id	sid	tid	token	lemma	pos
cana-6092	1	1	communications	communication	NOUN
cana-6092	1	2	on	on	ADP
cana-6092	1	3	applied	apply	VERB
cana-6092	1	4	nonlinear	nonlinear	ADJ
cana-6092	1	5	analysis	analysis	NOUN
cana-6092	1	6	issn	issn	NOUN
cana-6092	1	7	:	:	PUNCT
cana-6092	1	8	1074	1074	NUM
cana-6092	1	9	-	-	PUNCT
cana-6092	1	10	133x	133x	NUM
cana-6092	1	11	vol	vol	NOUN
cana-6092	1	12	31	31	NUM
cana-6092	1	13	no	no	NOUN
cana-6092	1	14	.	.	NOUN
cana-6092	1	15	2	2	NUM
cana-6092	1	16	(	(	PUNCT
cana-6092	1	17	2024	2024	NUM
cana-6092	1	18	)	)	PUNCT
cana-6092	1	19	499	499	NUM
cana-6092	1	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	1	21	a	a	DET
cana-6092	1	22	neural	neural	ADJ
cana-6092	1	23	network	network	NOUN
cana-6092	1	24	-	-	PUNCT
cana-6092	1	25	based	base	VERB
cana-6092	1	26	framework	framework	NOUN
cana-6092	1	27	for	for	ADP
cana-6092	1	28	solving	solve	VERB
cana-6092	1	29	large	large	ADJ
cana-6092	1	30	-	-	PUNCT
cana-6092	1	31	scale	scale	NOUN
cana-6092	1	32	inverse	inverse	NOUN
cana-6092	1	33	problems	problem	NOUN
cana-6092	1	34	shobhankumar	shobhankumar	VERB
cana-6092	1	35	d.m1	d.m1	NOUN
cana-6092	1	36	,	,	PUNCT
cana-6092	1	37	machhindranath	machhindranath	ADJ
cana-6092	1	38	m.	m.	NOUN
cana-6092	1	39	dhane2	dhane2	PROPN
cana-6092	1	40	*	*	PROPN
cana-6092	1	41	,	,	PUNCT
cana-6092	1	42	lakshmi	lakshmi	PROPN
cana-6092	1	43	janardhana	janardhana	PROPN
cana-6092	1	44	r.c3	r.c3	PROPN
cana-6092	1	45	,	,	PUNCT
cana-6092	1	46	vanaja	vanaja	PROPN
cana-6092	1	47	v4	v4	PROPN
cana-6092	1	48	.	.	PUNCT
cana-6092	2	1	1associate	1associate	NUM
cana-6092	2	2	professor	professor	NOUN
cana-6092	2	3	,	,	PUNCT
cana-6092	2	4	department	department	NOUN
cana-6092	2	5	of	of	ADP
cana-6092	2	6	mathematics	mathematics	PROPN
cana-6092	2	7	,	,	PUNCT
cana-6092	2	8	maharani	maharani	PROPN
cana-6092	2	9	’s	’s	PROPN
cana-6092	2	10	science	science	PROPN
cana-6092	2	11	college	college	PROPN
cana-6092	2	12	for	for	ADP
cana-6092	2	13	women	woman	NOUN
cana-6092	2	14	,	,	PUNCT
cana-6092	2	15	palace	palace	NOUN
cana-6092	2	16	road	road	NOUN
cana-6092	2	17	,	,	PUNCT
cana-6092	2	18	bengaluru	bengaluru	PROPN
cana-6092	2	19	,	,	PUNCT
cana-6092	2	20	karnataka	karnataka	PROPN
cana-6092	2	21	,	,	PUNCT
cana-6092	2	22	india	india	PROPN
cana-6092	2	23	;	;	PUNCT
cana-6092	2	24	email	email	NOUN
cana-6092	2	25	:	:	PUNCT
cana-6092	2	26	shobhankumardm@gmail.com	shobhankumardm@gmail.com	X
cana-6092	2	27	2*associate	2*associate	NUM
cana-6092	2	28	professor	professor	NOUN
cana-6092	2	29	,	,	PUNCT
cana-6092	2	30	department	department	NOUN
cana-6092	2	31	of	of	ADP
cana-6092	2	32	mathematics	mathematics	PROPN
cana-6092	2	33	,	,	PUNCT
cana-6092	2	34	gfgc	gfgc	PROPN
cana-6092	2	35	,	,	PUNCT
cana-6092	2	36	yelahanka	yelahanka	PROPN
cana-6092	2	37	,	,	PUNCT
cana-6092	2	38	bengaluru	bengaluru	PROPN
cana-6092	2	39	,	,	PUNCT
cana-6092	2	40	karnataka	karnataka	PROPN
cana-6092	2	41	,	,	PUNCT
cana-6092	2	42	india	india	PROPN
cana-6092	2	43	;	;	PUNCT
cana-6092	2	44	email	email	NOUN
cana-6092	2	45	:	:	PUNCT
cana-6092	2	46	drdhani.99dce@gmail.com	drdhani.99dce@gmail.com	NOUN
cana-6092	2	47	3	3	NUM
cana-6092	2	48	associate	associate	NOUN
cana-6092	2	49	professor	professor	NOUN
cana-6092	2	50	,	,	PUNCT
cana-6092	2	51	department	department	NOUN
cana-6092	2	52	of	of	ADP
cana-6092	2	53	mathematics	mathematics	PROPN
cana-6092	2	54	,	,	PUNCT
cana-6092	2	55	gfgc	gfgc	NOUN
cana-6092	2	56	,	,	PUNCT
cana-6092	2	57	vijayanagar	vijayanagar	NOUN
cana-6092	2	58	,	,	PUNCT
cana-6092	2	59	bengaluru	bengaluru	PROPN
cana-6092	2	60	,	,	PUNCT
cana-6092	2	61	karnataka	karnataka	PROPN
cana-6092	2	62	,	,	PUNCT
cana-6092	2	63	india	india	PROPN
cana-6092	2	64	;	;	PUNCT
cana-6092	2	65	email	email	NOUN
cana-6092	2	66	:	:	PUNCT
cana-6092	2	67	ljrcmaths@gmail.com	ljrcmaths@gmail.com	X
cana-6092	2	68	4	4	NUM
cana-6092	2	69	associate	associate	NOUN
cana-6092	2	70	professor	professor	NOUN
cana-6092	2	71	,	,	PUNCT
cana-6092	2	72	department	department	NOUN
cana-6092	2	73	of	of	ADP
cana-6092	2	74	mathematics	mathematics	PROPN
cana-6092	2	75	,	,	PUNCT
cana-6092	2	76	gfgc	gfgc	PROPN
cana-6092	2	77	,	,	PUNCT
cana-6092	2	78	yelahanka	yelahanka	PROPN
cana-6092	2	79	,	,	PUNCT
cana-6092	2	80	bengaluru	bengaluru	PROPN
cana-6092	2	81	,	,	PUNCT
cana-6092	2	82	karnataka	karnataka	PROPN
cana-6092	2	83	,	,	PUNCT
cana-6092	2	84	india	india	PROPN
cana-6092	2	85	;	;	PUNCT
cana-6092	2	86	email	email	NOUN
cana-6092	2	87	:	:	PUNCT
cana-6092	2	88	vanajaksr94@yahoo.com	vanajaksr94@yahoo.com	PROPN
cana-6092	2	89	*	*	PUNCT
cana-6092	2	90	corresponding	correspond	VERB
cana-6092	2	91	author	author	NOUN
cana-6092	2	92	:	:	PUNCT
cana-6092	2	93	drdhani.99dce@gmail.com	drdhani.99dce@gmail.com	X
cana-6092	2	94	email	email	NOUN
cana-6092	2	95	of	of	ADP
cana-6092	2	96	co	co	NOUN
cana-6092	2	97	-	-	NOUN
cana-6092	2	98	author	author	NOUN
cana-6092	2	99	:	:	PUNCT
cana-6092	2	100	shobhankumardm@gmail.com	shobhankumardm@gmail.com	X
cana-6092	2	101	article	article	NOUN
cana-6092	2	102	history	history	NOUN
cana-6092	2	103	:	:	PUNCT
cana-6092	2	104	received	receive	VERB
cana-6092	2	105	:	:	PUNCT
cana-6092	2	106	04	04	NUM
cana-6092	2	107	-	-	PUNCT
cana-6092	2	108	09	09	NUM
cana-6092	2	109	-	-	PUNCT
cana-6092	2	110	2024	2024	NUM
cana-6092	2	111	revised	revise	VERB
cana-6092	2	112	:	:	PUNCT
cana-6092	2	113	23	23	NUM
cana-6092	2	114	-	-	SYM
cana-6092	2	115	10	10	NUM
cana-6092	2	116	-	-	PUNCT
cana-6092	2	117	2024	2024	NUM
cana-6092	2	118	accepted	accept	VERB
cana-6092	2	119	:	:	PUNCT
cana-6092	2	120	26	26	NUM
cana-6092	2	121	-	-	SYM
cana-6092	2	122	11	11	NUM
cana-6092	2	123	-	-	PUNCT
cana-6092	2	124	2024	2024	NUM
cana-6092	2	125	abstract	abstract	NOUN
cana-6092	2	126	:	:	PUNCT
cana-6092	2	127	large	large	ADJ
cana-6092	2	128	-	-	PUNCT
cana-6092	2	129	scale	scale	NOUN
cana-6092	2	130	inverse	inverse	NOUN
cana-6092	2	131	problems	problem	NOUN
cana-6092	2	132	represent	represent	VERB
cana-6092	2	133	a	a	DET
cana-6092	2	134	class	class	NOUN
cana-6092	2	135	of	of	ADP
cana-6092	2	136	computational	computational	ADJ
cana-6092	2	137	challenges	challenge	NOUN
cana-6092	2	138	that	that	PRON
cana-6092	2	139	arise	arise	VERB
cana-6092	2	140	across	across	ADP
cana-6092	2	141	scientific	scientific	ADJ
cana-6092	2	142	and	and	CCONJ
cana-6092	2	143	engineering	engineering	NOUN
cana-6092	2	144	disciplines	discipline	NOUN
cana-6092	2	145	when	when	SCONJ
cana-6092	2	146	estimating	estimate	VERB
cana-6092	2	147	unknown	unknown	ADJ
cana-6092	2	148	system	system	NOUN
cana-6092	2	149	parameters	parameter	NOUN
cana-6092	2	150	from	from	ADP
cana-6092	2	151	observed	observed	ADJ
cana-6092	2	152	measurements	measurement	NOUN
cana-6092	2	153	.	.	PUNCT
cana-6092	3	1	these	these	DET
cana-6092	3	2	problems	problem	NOUN
cana-6092	3	3	are	be	AUX
cana-6092	3	4	typically	typically	ADV
cana-6092	3	5	ill	ill	ADV
cana-6092	3	6	-	-	PUNCT
cana-6092	3	7	posed	pose	VERB
cana-6092	3	8	and	and	CCONJ
cana-6092	3	9	computationally	computationally	ADV
cana-6092	3	10	demanding	demanding	ADJ
cana-6092	3	11	,	,	PUNCT
cana-6092	3	12	often	often	ADV
cana-6092	3	13	requiring	require	VERB
cana-6092	3	14	sophisticated	sophisticated	ADJ
cana-6092	3	15	regularization	regularization	NOUN
cana-6092	3	16	techniques	technique	NOUN
cana-6092	3	17	and	and	CCONJ
cana-6092	3	18	iterative	iterative	NOUN
cana-6092	3	19	optimization	optimization	NOUN
cana-6092	3	20	methods	method	NOUN
cana-6092	3	21	.	.	PUNCT
cana-6092	4	1	this	this	DET
cana-6092	4	2	paper	paper	NOUN
cana-6092	4	3	presents	present	VERB
cana-6092	4	4	a	a	DET
cana-6092	4	5	comprehensive	comprehensive	ADJ
cana-6092	4	6	neural	neural	ADJ
cana-6092	4	7	network	network	NOUN
cana-6092	4	8	-	-	PUNCT
cana-6092	4	9	based	base	VERB
cana-6092	4	10	framework	framework	NOUN
cana-6092	4	11	for	for	ADP
cana-6092	4	12	efficiently	efficiently	ADV
cana-6092	4	13	solving	solve	VERB
cana-6092	4	14	large	large	ADJ
cana-6092	4	15	-	-	PUNCT
cana-6092	4	16	scale	scale	NOUN
cana-6092	4	17	inverse	inverse	NOUN
cana-6092	4	18	problems	problem	NOUN
cana-6092	4	19	by	by	ADP
cana-6092	4	20	leveraging	leverage	VERB
cana-6092	4	21	recent	recent	ADJ
cana-6092	4	22	advances	advance	NOUN
cana-6092	4	23	in	in	ADP
cana-6092	4	24	deep	deep	ADJ
cana-6092	4	25	learning	learning	NOUN
cana-6092	4	26	architectures	architecture	NOUN
cana-6092	4	27	,	,	PUNCT
cana-6092	4	28	optimization	optimization	NOUN
cana-6092	4	29	strategies	strategy	NOUN
cana-6092	4	30	,	,	PUNCT
cana-6092	4	31	and	and	CCONJ
cana-6092	4	32	domain	domain	NOUN
cana-6092	4	33	-	-	PUNCT
cana-6092	4	34	specific	specific	ADJ
cana-6092	4	35	knowledge	knowledge	NOUN
cana-6092	4	36	incorporation	incorporation	NOUN
cana-6092	4	37	.	.	PUNCT
cana-6092	5	1	we	we	PRON
cana-6092	5	2	examine	examine	VERB
cana-6092	5	3	fundamental	fundamental	ADJ
cana-6092	5	4	theoretical	theoretical	ADJ
cana-6092	5	5	concepts	concept	NOUN
cana-6092	5	6	,	,	PUNCT
cana-6092	5	7	including	include	VERB
cana-6092	5	8	stability	stability	NOUN
cana-6092	5	9	-	-	PUNCT
cana-6092	5	10	accuracy	accuracy	NOUN
cana-6092	5	11	trade	trade	NOUN
cana-6092	5	12	-	-	PUNCT
cana-6092	5	13	offs	off	NOUN
cana-6092	5	14	in	in	ADP
cana-6092	5	15	neural	neural	ADJ
cana-6092	5	16	networks	network	NOUN
cana-6092	5	17	for	for	ADP
cana-6092	5	18	inverse	inverse	NOUN
cana-6092	5	19	problems	problem	NOUN
cana-6092	5	20	,	,	PUNCT
cana-6092	5	21	and	and	CCONJ
cana-6092	5	22	demonstrate	demonstrate	VERB
cana-6092	5	23	how	how	SCONJ
cana-6092	5	24	deep	deep	ADJ
cana-6092	5	25	learning	learning	NOUN
cana-6092	5	26	approaches	approach	NOUN
cana-6092	5	27	can	can	AUX
cana-6092	5	28	not	not	PART
cana-6092	5	29	only	only	ADV
cana-6092	5	30	accelerate	accelerate	VERB
cana-6092	5	31	solutions	solution	NOUN
cana-6092	5	32	but	but	CCONJ
cana-6092	5	33	also	also	ADV
cana-6092	5	34	achieve	achieve	VERB
cana-6092	5	35	superior	superior	ADJ
cana-6092	5	36	performance	performance	NOUN
cana-6092	5	37	compared	compare	VERB
cana-6092	5	38	to	to	ADP
cana-6092	5	39	traditional	traditional	ADJ
cana-6092	5	40	optimization	optimization	NOUN
cana-6092	5	41	methods	method	NOUN
cana-6092	5	42	.	.	PUNCT
cana-6092	6	1	the	the	DET
cana-6092	6	2	framework	framework	NOUN
cana-6092	6	3	integrates	integrate	VERB
cana-6092	6	4	physics	physics	NOUN
cana-6092	6	5	-	-	PUNCT
cana-6092	6	6	informed	inform	VERB
cana-6092	6	7	neural	neural	ADJ
cana-6092	6	8	networks	network	NOUN
cana-6092	6	9	,	,	PUNCT
cana-6092	6	10	generative	generative	ADJ
cana-6092	6	11	adversarial	adversarial	ADJ
cana-6092	6	12	networks	network	NOUN
cana-6092	6	13	,	,	PUNCT
cana-6092	6	14	and	and	CCONJ
cana-6092	6	15	differentiable	differentiable	ADJ
cana-6092	6	16	simulation	simulation	NOUN
cana-6092	6	17	techniques	technique	NOUN
cana-6092	6	18	to	to	PART
cana-6092	6	19	handle	handle	VERB
cana-6092	6	20	challenges	challenge	NOUN
cana-6092	6	21	such	such	ADJ
cana-6092	6	22	as	as	ADP
cana-6092	6	23	local	local	ADJ
cana-6092	6	24	minima	minima	NOUN
cana-6092	6	25	,	,	PUNCT
cana-6092	6	26	chaotic	chaotic	ADJ
cana-6092	6	27	behavior	behavior	NOUN
cana-6092	6	28	,	,	PUNCT
cana-6092	6	29	and	and	CCONJ
cana-6092	6	30	zero	zero	NUM
cana-6092	6	31	-	-	PUNCT
cana-6092	6	32	gradient	gradient	NOUN
cana-6092	6	33	regions	region	NOUN
cana-6092	6	34	that	that	PRON
cana-6092	6	35	plague	plague	VERB
cana-6092	6	36	conventional	conventional	ADJ
cana-6092	6	37	approaches	approach	NOUN
cana-6092	6	38	.	.	PUNCT
cana-6092	7	1	through	through	ADP
cana-6092	7	2	extensive	extensive	ADJ
cana-6092	7	3	analysis	analysis	NOUN
cana-6092	7	4	of	of	ADP
cana-6092	7	5	applications	application	NOUN
cana-6092	7	6	in	in	ADP
cana-6092	7	7	medical	medical	ADJ
cana-6092	7	8	imaging	imaging	NOUN
cana-6092	7	9	,	,	PUNCT
cana-6092	7	10	geophysical	geophysical	ADJ
cana-6092	7	11	inversion	inversion	NOUN
cana-6092	7	12	,	,	PUNCT
cana-6092	7	13	and	and	CCONJ
cana-6092	7	14	partial	partial	ADJ
cana-6092	7	15	differential	differential	NOUN
cana-6092	7	16	equation	equation	NOUN
cana-6092	7	17	(	(	PUNCT
cana-6092	7	18	pde)-based	pde)-base	VERB
cana-6092	7	19	problems	problem	NOUN
cana-6092	7	20	,	,	PUNCT
cana-6092	7	21	we	we	PRON
cana-6092	7	22	show	show	VERB
cana-6092	7	23	that	that	SCONJ
cana-6092	7	24	neural	neural	ADJ
cana-6092	7	25	network	network	NOUN
cana-6092	7	26	methods	method	NOUN
cana-6092	7	27	can	can	AUX
cana-6092	7	28	reduce	reduce	VERB
cana-6092	7	29	computational	computational	ADJ
cana-6092	7	30	costs	cost	NOUN
cana-6092	7	31	by	by	ADP
cana-6092	7	32	orders	order	NOUN
cana-6092	7	33	of	of	ADP
cana-6092	7	34	magnitude	magnitude	NOUN
cana-6092	7	35	while	while	SCONJ
cana-6092	7	36	maintaining	maintain	VERB
cana-6092	7	37	or	or	CCONJ
cana-6092	7	38	even	even	ADV
cana-6092	7	39	improving	improve	VERB
cana-6092	7	40	solution	solution	NOUN
cana-6092	7	41	quality	quality	NOUN
cana-6092	7	42	.	.	PUNCT
cana-6092	8	1	the	the	DET
cana-6092	8	2	paper	paper	NOUN
cana-6092	8	3	also	also	ADV
cana-6092	8	4	addresses	address	VERB
cana-6092	8	5	current	current	ADJ
cana-6092	8	6	limitations	limitation	NOUN
cana-6092	8	7	and	and	CCONJ
cana-6092	8	8	outlines	outline	VERB
cana-6092	8	9	future	future	ADJ
cana-6092	8	10	research	research	NOUN
cana-6092	8	11	directions	direction	NOUN
cana-6092	8	12	for	for	ADP
cana-6092	8	13	enhancing	enhance	VERB
cana-6092	8	14	the	the	DET
cana-6092	8	15	robustness	robustness	NOUN
cana-6092	8	16	,	,	PUNCT
cana-6092	8	17	scalability	scalability	NOUN
cana-6092	8	18	,	,	PUNCT
cana-6092	8	19	and	and	CCONJ
cana-6092	8	20	theoretical	theoretical	ADJ
cana-6092	8	21	understanding	understanding	NOUN
cana-6092	8	22	of	of	ADP
cana-6092	8	23	neural	neural	ADJ
cana-6092	8	24	network	network	NOUN
cana-6092	8	25	approaches	approach	NOUN
cana-6092	8	26	for	for	ADP
cana-6092	8	27	large	large	ADJ
cana-6092	8	28	-	-	PUNCT
cana-6092	8	29	scale	scale	NOUN
cana-6092	8	30	inverse	inverse	NOUN
cana-6092	8	31	problems	problem	NOUN
cana-6092	8	32	.	.	PUNCT
cana-6092	9	1	1.introduction	1.introduction	NUM
cana-6092	9	2	inverse	inverse	NOUN
cana-6092	9	3	problems	problem	NOUN
cana-6092	9	4	represent	represent	VERB
cana-6092	9	5	fundamental	fundamental	ADJ
cana-6092	9	6	challenges	challenge	NOUN
cana-6092	9	7	in	in	ADP
cana-6092	9	8	numerous	numerous	ADJ
cana-6092	9	9	scientific	scientific	ADJ
cana-6092	9	10	and	and	CCONJ
cana-6092	9	11	engineering	engineering	NOUN
cana-6092	9	12	domains	domain	NOUN
cana-6092	9	13	,	,	PUNCT
cana-6092	9	14	from	from	ADP
cana-6092	9	15	medical	medical	ADJ
cana-6092	9	16	imaging	imaging	NOUN
cana-6092	9	17	and	and	CCONJ
cana-6092	9	18	geophysical	geophysical	ADJ
cana-6092	9	19	exploration	exploration	NOUN
cana-6092	9	20	to	to	ADP
cana-6092	9	21	astronomical	astronomical	ADJ
cana-6092	9	22	imaging	imaging	NOUN
cana-6092	9	23	and	and	CCONJ
cana-6092	9	24	material	material	NOUN
cana-6092	9	25	science	science	NOUN
cana-6092	9	26	.	.	PUNCT
cana-6092	10	1	these	these	DET
cana-6092	10	2	problems	problem	NOUN
cana-6092	10	3	involve	involve	VERB
cana-6092	10	4	estimating	estimate	VERB
cana-6092	10	5	unknown	unknown	ADJ
cana-6092	10	6	system	system	NOUN
cana-6092	10	7	parameters	parameter	NOUN
cana-6092	10	8	or	or	CCONJ
cana-6092	10	9	hidden	hide	VERB
cana-6092	10	10	states	state	NOUN
cana-6092	10	11	from	from	ADP
cana-6092	10	12	observed	observed	ADJ
cana-6092	10	13	indirect	indirect	ADJ
cana-6092	10	14	measurements	measurement	NOUN
cana-6092	10	15	,	,	PUNCT
cana-6092	10	16	typically	typically	ADV
cana-6092	10	17	formulated	formulate	VERB
cana-6092	10	18	mailto:shobhankumardm@gmail.com	mailto:shobhankumardm@gmail.com	X
cana-6092	11	1	mailto:drdhani.99dce@gmail.com	mailto:drdhani.99dce@gmail.com	X
cana-6092	11	2	mailto:ljrcmaths@gmail.com	mailto:ljrcmaths@gmail.com	X
cana-6092	12	1	mailto:vanajaksr94@yahoo.com	mailto:vanajaksr94@yahoo.com	X
cana-6092	13	1	mailto:drdhani.99dce@gmail.com	mailto:drdhani.99dce@gmail.com	X
cana-6092	13	2	mailto:shobhankumardm@gmail.com	mailto:shobhankumardm@gmail.com	PROPN
cana-6092	13	3	communications	communication	NOUN
cana-6092	13	4	on	on	ADP
cana-6092	13	5	applied	apply	VERB
cana-6092	13	6	nonlinear	nonlinear	ADJ
cana-6092	13	7	analysis	analysis	NOUN
cana-6092	13	8	issn	issn	NOUN
cana-6092	13	9	:	:	PUNCT
cana-6092	13	10	1074	1074	NUM
cana-6092	13	11	-	-	PUNCT
cana-6092	13	12	133x	133x	NUM
cana-6092	13	13	vol	vol	NOUN
cana-6092	13	14	31	31	NUM
cana-6092	13	15	no	no	NOUN
cana-6092	13	16	.	.	NOUN
cana-6092	13	17	2	2	NUM
cana-6092	13	18	(	(	PUNCT
cana-6092	13	19	2024	2024	NUM
cana-6092	13	20	)	)	PUNCT
cana-6092	13	21	500	500	NUM
cana-6092	13	22	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	13	23	as	as	ADP
cana-6092	13	24	finding	find	VERB
cana-6092	13	25	parameters	parameter	NOUN
cana-6092	13	26	x	x	PUNCT
cana-6092	13	27	from	from	ADP
cana-6092	13	28	measurements	measurement	NOUN
cana-6092	13	29	y	y	PROPN
cana-6092	13	30	related	relate	VERB
cana-6092	13	31	through	through	ADP
cana-6092	13	32	a	a	DET
cana-6092	13	33	forward	forward	ADJ
cana-6092	13	34	model	model	NOUN
cana-6092	13	35	y	y	PROPN
cana-6092	13	36	=	=	SYM
cana-6092	13	37	f(x	f(x	PROPN
cana-6092	13	38	)	)	PUNCT
cana-6092	13	39	+	+	CCONJ
cana-6092	13	40	η	η	PROPN
cana-6092	13	41	,	,	PUNCT
cana-6092	13	42	where	where	SCONJ
cana-6092	13	43	f	f	PROPN
cana-6092	13	44	represents	represent	VERB
cana-6092	13	45	the	the	DET
cana-6092	13	46	physical	physical	ADJ
cana-6092	13	47	mapping	mapping	NOUN
cana-6092	13	48	and	and	CCONJ
cana-6092	13	49	η	η	PROPN
cana-6092	13	50	denotes	denotes	PROPN
cana-6092	13	51	measurement	measurement	NOUN
cana-6092	13	52	noise	noise	NOUN
cana-6092	13	53	13	13	NUM
cana-6092	13	54	.	.	PUNCT
cana-6092	14	1	large	large	ADJ
cana-6092	14	2	-	-	PUNCT
cana-6092	14	3	scale	scale	NOUN
cana-6092	14	4	inverse	inverse	NOUN
cana-6092	14	5	problems	problem	NOUN
cana-6092	14	6	are	be	AUX
cana-6092	14	7	characterized	characterize	VERB
cana-6092	14	8	by	by	ADP
cana-6092	14	9	highdimensional	highdimensional	ADJ
cana-6092	14	10	parameter	parameter	NOUN
cana-6092	14	11	spaces	space	NOUN
cana-6092	14	12	,	,	PUNCT
cana-6092	14	13	nonlinear	nonlinear	ADJ
cana-6092	14	14	relationships	relationship	NOUN
cana-6092	14	15	,	,	PUNCT
cana-6092	14	16	and	and	CCONJ
cana-6092	14	17	often	often	ADV
cana-6092	14	18	severe	severe	ADJ
cana-6092	14	19	ill	ill	ADJ
cana-6092	14	20	-	-	PUNCT
cana-6092	14	21	posedness	posedness	NOUN
cana-6092	14	22	,	,	PUNCT
cana-6092	14	23	meaning	mean	VERB
cana-6092	14	24	they	they	PRON
cana-6092	14	25	lack	lack	VERB
cana-6092	14	26	unique	unique	ADJ
cana-6092	14	27	solutions	solution	NOUN
cana-6092	14	28	or	or	CCONJ
cana-6092	14	29	exhibit	exhibit	VERB
cana-6092	14	30	extreme	extreme	ADJ
cana-6092	14	31	sensitivity	sensitivity	NOUN
cana-6092	14	32	to	to	PART
cana-6092	14	33	noise	noise	VERB
cana-6092	14	34	and	and	CCONJ
cana-6092	14	35	perturbations	perturbation	NOUN
cana-6092	14	36	in	in	ADP
cana-6092	14	37	measurements	measurement	NOUN
cana-6092	14	38	1	1	NUM
cana-6092	14	39	.	.	PUNCT
cana-6092	15	1	traditional	traditional	ADJ
cana-6092	15	2	approaches	approach	NOUN
cana-6092	15	3	to	to	ADP
cana-6092	15	4	solving	solve	VERB
cana-6092	15	5	inverse	inverse	NOUN
cana-6092	15	6	problems	problem	NOUN
cana-6092	15	7	include	include	VERB
cana-6092	15	8	analytical	analytical	ADJ
cana-6092	15	9	inversion	inversion	NOUN
cana-6092	15	10	methods	method	NOUN
cana-6092	15	11	,	,	PUNCT
cana-6092	15	12	iterative	iterative	ADJ
cana-6092	15	13	optimization	optimization	NOUN
cana-6092	15	14	techniques	technique	NOUN
cana-6092	15	15	,	,	PUNCT
cana-6092	15	16	variational	variational	ADJ
cana-6092	15	17	methods	method	NOUN
cana-6092	15	18	,	,	PUNCT
cana-6092	15	19	and	and	CCONJ
cana-6092	15	20	bayesian	bayesian	NOUN
cana-6092	15	21	inference	inference	NOUN
cana-6092	15	22	frameworks	framework	NOUN
cana-6092	15	23	.	.	PUNCT
cana-6092	16	1	while	while	SCONJ
cana-6092	16	2	these	these	DET
cana-6092	16	3	methods	method	NOUN
cana-6092	16	4	have	have	AUX
cana-6092	16	5	proven	prove	VERB
cana-6092	16	6	effective	effective	ADJ
cana-6092	16	7	in	in	ADP
cana-6092	16	8	many	many	ADJ
cana-6092	16	9	applications	application	NOUN
cana-6092	16	10	,	,	PUNCT
cana-6092	16	11	they	they	PRON
cana-6092	16	12	face	face	VERB
cana-6092	16	13	significant	significant	ADJ
cana-6092	16	14	limitations	limitation	NOUN
cana-6092	16	15	when	when	SCONJ
cana-6092	16	16	applied	apply	VERB
cana-6092	16	17	to	to	ADP
cana-6092	16	18	large	large	ADJ
cana-6092	16	19	-	-	PUNCT
cana-6092	16	20	scale	scale	NOUN
cana-6092	16	21	problems	problem	NOUN
cana-6092	16	22	:	:	PUNCT
cana-6092	16	23	they	they	PRON
cana-6092	16	24	require	require	VERB
cana-6092	16	25	explicitly	explicitly	ADV
cana-6092	16	26	defined	define	VERB
cana-6092	16	27	prior	prior	ADJ
cana-6092	16	28	models	model	NOUN
cana-6092	16	29	,	,	PUNCT
cana-6092	16	30	can	can	AUX
cana-6092	16	31	be	be	AUX
cana-6092	16	32	computationally	computationally	ADV
cana-6092	16	33	intensive	intensive	ADJ
cana-6092	16	34	for	for	ADP
cana-6092	16	35	high	high	ADJ
cana-6092	16	36	-	-	PUNCT
cana-6092	16	37	dimensional	dimensional	ADJ
cana-6092	16	38	spaces	space	NOUN
cana-6092	16	39	,	,	PUNCT
cana-6092	16	40	may	may	AUX
cana-6092	16	41	struggle	struggle	VERB
cana-6092	16	42	with	with	ADP
cana-6092	16	43	complex	complex	ADJ
cana-6092	16	44	non	non	ADJ
cana-6092	16	45	-	-	ADJ
cana-6092	16	46	gaussian	gaussian	ADJ
cana-6092	16	47	distributions	distribution	NOUN
cana-6092	16	48	,	,	PUNCT
cana-6092	16	49	and	and	CCONJ
cana-6092	16	50	typically	typically	ADV
cana-6092	16	51	need	need	VERB
cana-6092	16	52	customization	customization	NOUN
cana-6092	16	53	for	for	ADP
cana-6092	16	54	each	each	DET
cana-6092	16	55	specific	specific	ADJ
cana-6092	16	56	problem	problem	NOUN
cana-6092	16	57	type	type	NOUN
cana-6092	16	58	13	13	NUM
cana-6092	16	59	.	.	PUNCT
cana-6092	17	1	the	the	DET
cana-6092	17	2	computational	computational	ADJ
cana-6092	17	3	burden	burden	NOUN
cana-6092	17	4	is	be	AUX
cana-6092	17	5	particularly	particularly	ADV
cana-6092	17	6	prohibitive	prohibitive	ADJ
cana-6092	17	7	in	in	ADP
cana-6092	17	8	applications	application	NOUN
cana-6092	17	9	requiring	require	VERB
cana-6092	17	10	real	real	ADJ
cana-6092	17	11	-	-	PUNCT
cana-6092	17	12	time	time	NOUN
cana-6092	17	13	solutions	solution	NOUN
cana-6092	17	14	or	or	CCONJ
cana-6092	17	15	dealing	deal	VERB
cana-6092	17	16	with	with	ADP
cana-6092	17	17	extremely	extremely	ADV
cana-6092	17	18	high	high	ADJ
cana-6092	17	19	-	-	PUNCT
cana-6092	17	20	dimensional	dimensional	ADJ
cana-6092	17	21	parameter	parameter	NOUN
cana-6092	17	22	spaces	space	NOUN
cana-6092	17	23	.	.	PUNCT
cana-6092	18	1	the	the	DET
cana-6092	18	2	emergence	emergence	NOUN
cana-6092	18	3	of	of	ADP
cana-6092	18	4	deep	deep	ADJ
cana-6092	18	5	learning	learning	NOUN
cana-6092	18	6	methodologies	methodology	NOUN
cana-6092	18	7	has	have	AUX
cana-6092	18	8	introduced	introduce	VERB
cana-6092	18	9	transformative	transformative	ADJ
cana-6092	18	10	new	new	ADJ
cana-6092	18	11	paradigms	paradigm	NOUN
cana-6092	18	12	for	for	ADP
cana-6092	18	13	addressing	address	VERB
cana-6092	18	14	large	large	ADJ
cana-6092	18	15	-	-	PUNCT
cana-6092	18	16	scale	scale	NOUN
cana-6092	18	17	inverse	inverse	NOUN
cana-6092	18	18	problems	problem	NOUN
cana-6092	18	19	.	.	PUNCT
cana-6092	19	1	neural	neural	ADJ
cana-6092	19	2	networks	network	NOUN
cana-6092	19	3	offer	offer	VERB
cana-6092	19	4	several	several	ADJ
cana-6092	19	5	compelling	compelling	ADJ
cana-6092	19	6	advantages	advantage	NOUN
cana-6092	19	7	:	:	PUNCT
cana-6092	19	8	(	(	PUNCT
cana-6092	19	9	1	1	X
cana-6092	19	10	)	)	PUNCT
cana-6092	19	11	the	the	DET
cana-6092	19	12	ability	ability	NOUN
cana-6092	19	13	to	to	PART
cana-6092	19	14	learn	learn	VERB
cana-6092	19	15	data	data	NOUN
cana-6092	19	16	-	-	PUNCT
cana-6092	19	17	driven	drive	VERB
cana-6092	19	18	priors	prior	NOUN
cana-6092	19	19	that	that	PRON
cana-6092	19	20	capture	capture	VERB
cana-6092	19	21	complex	complex	ADJ
cana-6092	19	22	structures	structure	NOUN
cana-6092	19	23	more	more	ADV
cana-6092	19	24	effectively	effectively	ADV
cana-6092	19	25	than	than	ADP
cana-6092	19	26	hand	hand	NOUN
cana-6092	19	27	-	-	PUNCT
cana-6092	19	28	crafted	craft	VERB
cana-6092	19	29	regularizers	regularizer	NOUN
cana-6092	19	30	;	;	PUNCT
cana-6092	19	31	(	(	PUNCT
cana-6092	19	32	2	2	X
cana-6092	19	33	)	)	PUNCT
cana-6092	19	34	accelerated	accelerate	VERB
cana-6092	19	35	computation	computation	NOUN
cana-6092	19	36	through	through	ADP
cana-6092	19	37	direct	direct	ADJ
cana-6092	19	38	mapping	mapping	NOUN
cana-6092	19	39	from	from	ADP
cana-6092	19	40	measurements	measurement	NOUN
cana-6092	19	41	to	to	ADP
cana-6092	19	42	parameters	parameter	NOUN
cana-6092	19	43	once	once	ADV
cana-6092	19	44	trained	train	VERB
cana-6092	19	45	;	;	PUNCT
cana-6092	19	46	(	(	PUNCT
cana-6092	19	47	3	3	X
cana-6092	19	48	)	)	PUNCT
cana-6092	19	49	improved	improve	VERB
cana-6092	19	50	handling	handling	NOUN
cana-6092	19	51	of	of	ADP
cana-6092	19	52	non	non	ADJ
cana-6092	19	53	-	-	ADJ
cana-6092	19	54	gaussian	gaussian	ADJ
cana-6092	19	55	uncertainties	uncertainty	NOUN
cana-6092	19	56	and	and	CCONJ
cana-6092	19	57	multi	multi	ADJ
cana-6092	19	58	-	-	ADJ
cana-6092	19	59	modal	modal	ADJ
cana-6092	19	60	distributions	distribution	NOUN
cana-6092	19	61	;	;	PUNCT
cana-6092	19	62	and	and	CCONJ
cana-6092	19	63	(	(	PUNCT
cana-6092	19	64	4	4	X
cana-6092	19	65	)	)	PUNCT
cana-6092	19	66	potential	potential	NOUN
cana-6092	19	67	for	for	ADP
cana-6092	19	68	unsupervised	unsupervised	ADJ
cana-6092	19	69	or	or	CCONJ
cana-6092	19	70	semisupervised	semisupervised	ADJ
cana-6092	19	71	learning	learning	NOUN
cana-6092	19	72	paradigms	paradigm	NOUN
cana-6092	19	73	that	that	PRON
cana-6092	19	74	reduce	reduce	VERB
cana-6092	19	75	reliance	reliance	NOUN
cana-6092	19	76	on	on	ADP
cana-6092	19	77	fully	fully	ADV
cana-6092	19	78	-	-	PUNCT
cana-6092	19	79	labeled	label	VERB
cana-6092	19	80	training	training	NOUN
cana-6092	19	81	data	datum	NOUN
cana-6092	19	82	23	23	NUM
cana-6092	19	83	.	.	PUNCT
cana-6092	20	1	recent	recent	ADJ
cana-6092	20	2	work	work	NOUN
cana-6092	20	3	has	have	AUX
cana-6092	20	4	demonstrated	demonstrate	VERB
cana-6092	20	5	that	that	SCONJ
cana-6092	20	6	neural	neural	ADJ
cana-6092	20	7	networks	network	NOUN
cana-6092	20	8	can	can	AUX
cana-6092	20	9	not	not	PART
cana-6092	20	10	only	only	ADV
cana-6092	20	11	accelerate	accelerate	VERB
cana-6092	20	12	solutions	solution	NOUN
cana-6092	20	13	but	but	CCONJ
cana-6092	20	14	also	also	ADV
cana-6092	20	15	find	find	VERB
cana-6092	20	16	better	well	ADJ
cana-6092	20	17	solutions	solution	NOUN
cana-6092	20	18	than	than	ADP
cana-6092	20	19	classical	classical	ADJ
cana-6092	20	20	optimizers	optimizer	NOUN
cana-6092	20	21	,	,	PUNCT
cana-6092	20	22	even	even	ADV
cana-6092	20	23	on	on	ADP
cana-6092	20	24	their	their	PRON
cana-6092	20	25	training	training	NOUN
cana-6092	20	26	set	set	NOUN
cana-6092	20	27	,	,	PUNCT
cana-6092	20	28	particularly	particularly	ADV
cana-6092	20	29	for	for	ADP
cana-6092	20	30	problems	problem	NOUN
cana-6092	20	31	with	with	ADP
cana-6092	20	32	local	local	ADJ
cana-6092	20	33	minima	minima	PROPN
cana-6092	20	34	,	,	PUNCT
cana-6092	20	35	chaos	chaos	NOUN
cana-6092	20	36	,	,	PUNCT
cana-6092	20	37	and	and	CCONJ
cana-6092	20	38	zero	zero	NUM
cana-6092	20	39	-	-	PUNCT
cana-6092	20	40	gradient	gradient	NOUN
cana-6092	20	41	regions	region	NOUN
cana-6092	20	42	23	23	NUM
cana-6092	20	43	.	.	PUNCT
cana-6092	21	1	this	this	DET
cana-6092	21	2	paper	paper	NOUN
cana-6092	21	3	presents	present	VERB
cana-6092	21	4	a	a	DET
cana-6092	21	5	comprehensive	comprehensive	ADJ
cana-6092	21	6	neural	neural	ADJ
cana-6092	21	7	network	network	NOUN
cana-6092	21	8	-	-	PUNCT
cana-6092	21	9	based	base	VERB
cana-6092	21	10	framework	framework	NOUN
cana-6092	21	11	for	for	ADP
cana-6092	21	12	solving	solve	VERB
cana-6092	21	13	large	large	ADJ
cana-6092	21	14	-	-	PUNCT
cana-6092	21	15	scale	scale	NOUN
cana-6092	21	16	inverse	inverse	NOUN
cana-6092	21	17	problems	problem	NOUN
cana-6092	21	18	,	,	PUNCT
cana-6092	21	19	addressing	address	VERB
cana-6092	21	20	both	both	DET
cana-6092	21	21	theoretical	theoretical	ADJ
cana-6092	21	22	foundations	foundation	NOUN
cana-6092	21	23	and	and	CCONJ
cana-6092	21	24	practical	practical	ADJ
cana-6092	21	25	implementations	implementation	NOUN
cana-6092	21	26	.	.	PUNCT
cana-6092	22	1	we	we	PRON
cana-6092	22	2	examine	examine	VERB
cana-6092	22	3	various	various	ADJ
cana-6092	22	4	architectures	architecture	NOUN
cana-6092	22	5	,	,	PUNCT
cana-6092	22	6	including	include	VERB
cana-6092	22	7	physicsinformed	physicsinforme	VERB
cana-6092	22	8	neural	neural	ADJ
cana-6092	22	9	networks	network	NOUN
cana-6092	22	10	(	(	PUNCT
cana-6092	22	11	pinns	pinn	NOUN
cana-6092	22	12	)	)	PUNCT
cana-6092	22	13	,	,	PUNCT
cana-6092	22	14	generative	generative	ADJ
cana-6092	22	15	adversarial	adversarial	ADJ
cana-6092	22	16	networks	network	NOUN
cana-6092	22	17	(	(	PUNCT
cana-6092	22	18	gans	gan	NOUN
cana-6092	22	19	)	)	PUNCT
cana-6092	22	20	,	,	PUNCT
cana-6092	22	21	and	and	CCONJ
cana-6092	22	22	differentiable	differentiable	ADJ
cana-6092	22	23	simulation	simulation	NOUN
cana-6092	22	24	approaches	approach	NOUN
cana-6092	22	25	,	,	PUNCT
cana-6092	22	26	and	and	CCONJ
cana-6092	22	27	analyze	analyze	VERB
cana-6092	22	28	their	their	PRON
cana-6092	22	29	performance	performance	NOUN
cana-6092	22	30	across	across	ADP
cana-6092	22	31	diverse	diverse	ADJ
cana-6092	22	32	application	application	NOUN
cana-6092	22	33	domains	domain	NOUN
cana-6092	22	34	.	.	PUNCT
cana-6092	23	1	through	through	ADP
cana-6092	23	2	this	this	DET
cana-6092	23	3	analysis	analysis	NOUN
cana-6092	23	4	,	,	PUNCT
cana-6092	23	5	we	we	PRON
cana-6092	23	6	aim	aim	VERB
cana-6092	23	7	to	to	PART
cana-6092	23	8	provide	provide	VERB
cana-6092	23	9	researchers	researcher	NOUN
cana-6092	23	10	and	and	CCONJ
cana-6092	23	11	practitioners	practitioner	NOUN
cana-6092	23	12	with	with	ADP
cana-6092	23	13	insights	insight	NOUN
cana-6092	23	14	into	into	ADP
cana-6092	23	15	selecting	selecting	NOUN
cana-6092	23	16	,	,	PUNCT
cana-6092	23	17	designing	designing	NOUN
cana-6092	23	18	,	,	PUNCT
cana-6092	23	19	and	and	CCONJ
cana-6092	23	20	implementing	implement	VERB
cana-6092	23	21	neural	neural	ADJ
cana-6092	23	22	network	network	NOUN
cana-6092	23	23	approaches	approach	NOUN
cana-6092	23	24	for	for	ADP
cana-6092	23	25	large	large	ADJ
cana-6092	23	26	-	-	PUNCT
cana-6092	23	27	scale	scale	NOUN
cana-6092	23	28	inverse	inverse	NOUN
cana-6092	23	29	problems	problem	NOUN
cana-6092	23	30	while	while	SCONJ
cana-6092	23	31	understanding	understand	VERB
cana-6092	23	32	current	current	ADJ
cana-6092	23	33	limitations	limitation	NOUN
cana-6092	23	34	and	and	CCONJ
cana-6092	23	35	future	future	ADJ
cana-6092	23	36	research	research	NOUN
cana-6092	23	37	directions	direction	NOUN
cana-6092	23	38	.	.	PUNCT
cana-6092	24	1	2.theoretical	2.theoretical	NUM
cana-6092	24	2	foundations	foundation	NOUN
cana-6092	24	3	2.1	2.1	NUM
cana-6092	24	4	mathematical	mathematical	ADJ
cana-6092	24	5	formulation	formulation	NOUN
cana-6092	24	6	of	of	ADP
cana-6092	24	7	inverse	inverse	NOUN
cana-6092	24	8	problems	problem	NOUN
cana-6092	24	9	the	the	DET
cana-6092	24	10	mathematical	mathematical	ADJ
cana-6092	24	11	formulation	formulation	NOUN
cana-6092	24	12	of	of	ADP
cana-6092	24	13	inverse	inverse	NOUN
cana-6092	24	14	problems	problem	NOUN
cana-6092	24	15	typically	typically	ADV
cana-6092	24	16	begins	begin	VERB
cana-6092	24	17	with	with	ADP
cana-6092	24	18	a	a	DET
cana-6092	24	19	forward	forward	ADJ
cana-6092	24	20	model	model	NOUN
cana-6092	24	21	that	that	PRON
cana-6092	24	22	describes	describe	VERB
cana-6092	24	23	how	how	SCONJ
cana-6092	24	24	system	system	NOUN
cana-6092	24	25	parameters	parameter	NOUN
cana-6092	24	26	generate	generate	VERB
cana-6092	24	27	observable	observable	ADJ
cana-6092	24	28	measurements	measurement	NOUN
cana-6092	24	29	.	.	PUNCT
cana-6092	25	1	given	give	VERB
cana-6092	25	2	a	a	DET
cana-6092	25	3	forward	forward	ADJ
cana-6092	25	4	operator	operator	NOUN
cana-6092	25	5	f	f	NOUN
cana-6092	25	6	:	:	PUNCT
cana-6092	26	1	ℝⁿ	ℝⁿ	X
cana-6092	26	2	→	→	PUNCT
cana-6092	26	3	ℝᵐ	ℝᵐ	NOUN
cana-6092	26	4	that	that	PRON
cana-6092	26	5	maps	map	VERB
cana-6092	26	6	parameters	parameter	NOUN
cana-6092	26	7	x	x	X
cana-6092	26	8	∈	∈	PRON
cana-6092	27	1	ℝⁿ	ℝⁿ	ADV
cana-6092	27	2	to	to	ADP
cana-6092	27	3	measurements	measurement	NOUN
cana-6092	27	4	y	y	PROPN
cana-6092	27	5	∈	∈	PROPN
cana-6092	27	6	ℝᵐ	ℝᵐ	PROPN
cana-6092	27	7	,	,	PUNCT
cana-6092	27	8	the	the	DET
cana-6092	27	9	inverse	inverse	NOUN
cana-6092	27	10	problem	problem	NOUN
cana-6092	27	11	involves	involve	VERB
cana-6092	27	12	estimating	estimate	VERB
cana-6092	27	13	*	*	PUNCT
cana-6092	27	14	x	x	X
cana-6092	27	15	*	*	PUNCT
cana-6092	27	16	from	from	ADP
cana-6092	27	17	noisy	noisy	ADJ
cana-6092	27	18	observations	observation	NOUN
cana-6092	27	19	:	:	PUNCT
cana-6092	27	20	y	y	PROPN
cana-6092	27	21	=	=	SYM
cana-6092	27	22	f(x	f(x	PROPN
cana-6092	27	23	)	)	PUNCT
cana-6092	28	1	+	+	CCONJ
cana-6092	28	2	η	η	PROPN
cana-6092	28	3	where	where	SCONJ
cana-6092	28	4	η	η	PROPN
cana-6092	28	5	represents	represent	VERB
cana-6092	28	6	measurement	measurement	NOUN
cana-6092	28	7	noise	noise	NOUN
cana-6092	28	8	,	,	PUNCT
cana-6092	28	9	often	often	ADV
cana-6092	28	10	assumed	assume	VERB
cana-6092	28	11	to	to	PART
cana-6092	28	12	be	be	AUX
cana-6092	28	13	gaussian	gaussian	ADJ
cana-6092	28	14	with	with	ADP
cana-6092	28	15	zero	zero	NUM
cana-6092	28	16	mean	mean	NOUN
cana-6092	28	17	and	and	CCONJ
cana-6092	28	18	known	known	ADJ
cana-6092	28	19	covariance	covariance	NOUN
cana-6092	28	20	13	13	NUM
cana-6092	28	21	.	.	PUNCT
cana-6092	29	1	inverse	inverse	NOUN
cana-6092	29	2	problems	problem	NOUN
cana-6092	29	3	are	be	AUX
cana-6092	29	4	ill	ill	ADV
cana-6092	29	5	-	-	PUNCT
cana-6092	29	6	posed	pose	VERB
cana-6092	29	7	in	in	ADP
cana-6092	29	8	the	the	DET
cana-6092	29	9	sense	sense	NOUN
cana-6092	29	10	of	of	ADP
cana-6092	29	11	hadamard	hadamard	NOUN
cana-6092	29	12	,	,	PUNCT
cana-6092	29	13	violating	violate	VERB
cana-6092	29	14	at	at	ADV
cana-6092	29	15	least	least	ADJ
cana-6092	29	16	one	one	NUM
cana-6092	29	17	of	of	ADP
cana-6092	29	18	the	the	DET
cana-6092	29	19	conditions	condition	NOUN
cana-6092	29	20	for	for	ADP
cana-6092	29	21	well	well	ADV
cana-6092	29	22	-	-	PUNCT
cana-6092	29	23	posedness	posedness	NOUN
cana-6092	29	24	:	:	PUNCT
cana-6092	30	1	existence	existence	NOUN
cana-6092	30	2	,	,	PUNCT
cana-6092	30	3	uniqueness	uniqueness	NOUN
cana-6092	30	4	,	,	PUNCT
cana-6092	30	5	and	and	CCONJ
cana-6092	30	6	stability	stability	NOUN
cana-6092	30	7	of	of	ADP
cana-6092	30	8	solutions	solution	NOUN
cana-6092	30	9	1	1	NUM
cana-6092	30	10	.	.	PUNCT
cana-6092	31	1	this	this	DET
cana-6092	31	2	ill	ill	ADJ
cana-6092	31	3	-	-	PUNCT
cana-6092	31	4	posedness	posedness	NOUN
cana-6092	31	5	arises	arise	VERB
cana-6092	31	6	from	from	ADP
cana-6092	31	7	various	various	ADJ
cana-6092	31	8	factors	factor	NOUN
cana-6092	31	9	including	include	VERB
cana-6092	31	10	noise	noise	NOUN
cana-6092	31	11	in	in	ADP
cana-6092	31	12	measurements	measurement	NOUN
cana-6092	31	13	,	,	PUNCT
cana-6092	31	14	incomplete	incomplete	ADJ
cana-6092	31	15	data	datum	NOUN
cana-6092	31	16	(	(	PUNCT
cana-6092	31	17	e.g.	e.g.	ADV
cana-6092	31	18	,	,	PUNCT
cana-6092	31	19	limited	limited	ADJ
cana-6092	31	20	viewing	view	VERB
cana-6092	31	21	angles	angle	NOUN
cana-6092	31	22	in	in	ADP
cana-6092	31	23	tomography	tomography	NOUN
cana-6092	31	24	)	)	PUNCT
cana-6092	31	25	,	,	PUNCT
cana-6092	31	26	and	and	CCONJ
cana-6092	31	27	the	the	DET
cana-6092	31	28	inherent	inherent	ADJ
cana-6092	31	29	null	null	ADJ
cana-6092	31	30	space	space	NOUN
cana-6092	31	31	of	of	ADP
cana-6092	31	32	the	the	DET
cana-6092	31	33	forward	forward	ADJ
cana-6092	31	34	operator	operator	NOUN
cana-6092	31	35	where	where	SCONJ
cana-6092	31	36	different	different	ADJ
cana-6092	31	37	parameters	parameter	NOUN
cana-6092	31	38	produce	produce	VERB
cana-6092	31	39	identical	identical	ADJ
cana-6092	31	40	measurements	measurement	NOUN
cana-6092	31	41	.	.	PUNCT
cana-6092	32	1	to	to	PART
cana-6092	32	2	address	address	VERB
cana-6092	32	3	ill	ill	ADJ
cana-6092	32	4	-	-	PUNCT
cana-6092	32	5	posedness	posedness	NOUN
cana-6092	32	6	,	,	PUNCT
cana-6092	32	7	regularization	regularization	NOUN
cana-6092	32	8	techniques	technique	NOUN
cana-6092	32	9	introduce	introduce	VERB
cana-6092	32	10	additional	additional	ADJ
cana-6092	32	11	constraints	constraint	NOUN
cana-6092	32	12	based	base	VERB
cana-6092	32	13	on	on	ADP
cana-6092	32	14	prior	prior	ADJ
cana-6092	32	15	knowledge	knowledge	NOUN
cana-6092	32	16	about	about	ADP
cana-6092	32	17	the	the	DET
cana-6092	32	18	solution	solution	NOUN
cana-6092	32	19	.	.	PUNCT
cana-6092	33	1	the	the	DET
cana-6092	33	2	variational	variational	ADJ
cana-6092	33	3	approach	approach	NOUN
cana-6092	33	4	formulates	formulate	VERB
cana-6092	33	5	inversion	inversion	NOUN
cana-6092	33	6	as	as	ADP
cana-6092	33	7	an	an	DET
cana-6092	33	8	optimization	optimization	NOUN
cana-6092	33	9	problem	problem	NOUN
cana-6092	33	10	:	:	PUNCT
cana-6092	33	11	x̂	x̂	X
cana-6092	33	12	=	=	PUNCT
cana-6092	33	13	argminₓ	argminₓ	PROPN
cana-6092	33	14	[	[	PUNCT
cana-6092	33	15	||y	||y	ADJ
cana-6092	33	16	f(x)||²	f(x)||²	PROPN
cana-6092	33	17	+	+	CCONJ
cana-6092	33	18	λr(x	λr(x	NOUN
cana-6092	33	19	)	)	PUNCT
cana-6092	33	20	]	]	PUNCT
cana-6092	33	21	where	where	SCONJ
cana-6092	33	22	the	the	DET
cana-6092	33	23	first	first	ADJ
cana-6092	33	24	term	term	NOUN
cana-6092	33	25	ensures	ensure	VERB
cana-6092	33	26	data	datum	NOUN
cana-6092	33	27	fidelity	fidelity	NOUN
cana-6092	33	28	,	,	PUNCT
cana-6092	33	29	r(x	r(x	PROPN
cana-6092	33	30	)	)	PUNCT
cana-6092	33	31	is	be	AUX
cana-6092	33	32	the	the	DET
cana-6092	33	33	regularization	regularization	NOUN
cana-6092	33	34	term	term	NOUN
cana-6092	33	35	incorporating	incorporate	VERB
cana-6092	33	36	prior	prior	ADJ
cana-6092	33	37	knowledge	knowledge	NOUN
cana-6092	33	38	,	,	PUNCT
cana-6092	33	39	and	and	CCONJ
cana-6092	33	40	λ	λ	PROPN
cana-6092	33	41	controls	control	VERB
cana-6092	33	42	the	the	DET
cana-6092	33	43	trade	trade	NOUN
cana-6092	33	44	-	-	PUNCT
cana-6092	33	45	off	off	NOUN
cana-6092	33	46	between	between	ADP
cana-6092	33	47	data	datum	NOUN
cana-6092	33	48	fitting	fitting	ADJ
cana-6092	33	49	and	and	CCONJ
cana-6092	33	50	regularization	regularization	NOUN
cana-6092	33	51	1	1	NUM
cana-6092	33	52	.	.	PUNCT
cana-6092	34	1	common	common	ADJ
cana-6092	34	2	regularizers	regularizer	NOUN
cana-6092	34	3	include	include	VERB
cana-6092	34	4	tikhonov	tikhonov	NOUN
cana-6092	34	5	(	(	PUNCT
cana-6092	34	6	l₂	l₂	NOUN
cana-6092	34	7	)	)	PUNCT
cana-6092	34	8	regularization	regularization	NOUN
cana-6092	34	9	promoting	promote	VERB
cana-6092	34	10	smoothness	smoothness	NOUN
cana-6092	34	11	,	,	PUNCT
cana-6092	34	12	total	total	ADJ
cana-6092	34	13	variation	variation	NOUN
cana-6092	34	14	(	(	PUNCT
cana-6092	34	15	tv	tv	NOUN
cana-6092	34	16	)	)	PUNCT
cana-6092	34	17	regularization	regularization	NOUN
cana-6092	34	18	preserving	preserve	VERB
cana-6092	34	19	edges	edge	NOUN
cana-6092	34	20	,	,	PUNCT
cana-6092	34	21	and	and	CCONJ
cana-6092	34	22	sparsity	sparsity	NOUN
cana-6092	34	23	-	-	PUNCT
cana-6092	34	24	promoting	promote	VERB
cana-6092	34	25	regularizers	regularizer	NOUN
cana-6092	34	26	using	use	VERB
cana-6092	34	27	l₁	l₁	NOUN
cana-6092	34	28	norms	norm	NOUN
cana-6092	34	29	.	.	PUNCT
cana-6092	35	1	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	PROPN
cana-6092	35	2	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	35	3	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	PROPN
cana-6092	35	4	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	35	5	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	35	6	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	PROPN
cana-6092	35	7	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	35	8	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	PROPN
cana-6092	35	9	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	35	10	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	35	11	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	35	12	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	35	13	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	35	14	communications	communication	NOUN
cana-6092	35	15	on	on	ADP
cana-6092	35	16	applied	apply	VERB
cana-6092	35	17	nonlinear	nonlinear	ADJ
cana-6092	35	18	analysis	analysis	NOUN
cana-6092	35	19	issn	issn	NOUN
cana-6092	35	20	:	:	PUNCT
cana-6092	35	21	1074	1074	NUM
cana-6092	35	22	-	-	PUNCT
cana-6092	35	23	133x	133x	NUM
cana-6092	35	24	vol	vol	NOUN
cana-6092	35	25	31	31	NUM
cana-6092	35	26	no	no	NOUN
cana-6092	35	27	.	.	NOUN
cana-6092	35	28	2	2	NUM
cana-6092	35	29	(	(	PUNCT
cana-6092	35	30	2024	2024	NUM
cana-6092	35	31	)	)	PUNCT
cana-6092	35	32	501	501	NUM
cana-6092	35	33	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	35	34	2.2	2.2	NUM
cana-6092	35	35	neural	neural	ADJ
cana-6092	35	36	networks	network	NOUN
cana-6092	35	37	for	for	ADP
cana-6092	35	38	inverse	inverse	NOUN
cana-6092	35	39	problems	problem	NOUN
cana-6092	35	40	neural	neural	ADJ
cana-6092	35	41	networks	network	NOUN
cana-6092	35	42	approach	approach	VERB
cana-6092	35	43	inverse	inverse	NOUN
cana-6092	35	44	problems	problem	NOUN
cana-6092	35	45	through	through	ADP
cana-6092	35	46	two	two	NUM
cana-6092	35	47	primary	primary	ADJ
cana-6092	35	48	paradigms	paradigm	NOUN
cana-6092	35	49	:	:	PUNCT
cana-6092	35	50	(	(	PUNCT
cana-6092	35	51	1	1	X
cana-6092	35	52	)	)	PUNCT
cana-6092	35	53	learning	learn	VERB
cana-6092	35	54	direct	direct	ADJ
cana-6092	35	55	inverse	inverse	NOUN
cana-6092	35	56	mappings	mapping	NOUN
cana-6092	35	57	from	from	ADP
cana-6092	35	58	measurements	measurement	NOUN
cana-6092	35	59	to	to	ADP
cana-6092	35	60	parameters	parameter	NOUN
cana-6092	35	61	,	,	PUNCT
cana-6092	35	62	and	and	CCONJ
cana-6092	35	63	(	(	PUNCT
cana-6092	35	64	2	2	X
cana-6092	35	65	)	)	PUNCT
cana-6092	35	66	learning	learn	VERB
cana-6092	35	67	iterative	iterative	ADJ
cana-6092	35	68	reconstruction	reconstruction	NOUN
cana-6092	35	69	algorithms	algorithm	NOUN
cana-6092	35	70	that	that	PRON
cana-6092	35	71	incorporate	incorporate	VERB
cana-6092	35	72	physical	physical	ADJ
cana-6092	35	73	models	model	NOUN
cana-6092	35	74	23	23	NUM
cana-6092	35	75	.	.	PUNCT
cana-6092	36	1	consider	consider	VERB
cana-6092	36	2	a	a	DET
cana-6092	36	3	set	set	NOUN
cana-6092	36	4	of	of	ADP
cana-6092	36	5	n	n	PRON
cana-6092	36	6	inverse	inverse	NOUN
cana-6092	36	7	problems	problem	NOUN
cana-6092	36	8	:	:	PUNCT
cana-6092	36	9	x_i^	x_i^	X
cana-6092	36	10	=	=	SYM
cana-6092	36	11	argmin_{x_i	argmin_{x_i	PROPN
cana-6092	36	12	}	}	PUNCT
cana-6092	36	13	ℒ(f(x_i	ℒ(f(x_i	X
cana-6092	36	14	|	|	ADV
cana-6092	36	15	γ_i	γ_i	NOUN
cana-6092	36	16	)	)	PUNCT
cana-6092	36	17	,	,	PUNCT
cana-6092	36	18	y_i	y_i	NUM
cana-6092	36	19	)	)	PUNCT
cana-6092	36	20	each	each	DET
cana-6092	36	21	parameterized	parameterized	ADJ
cana-6092	36	22	by	by	ADP
cana-6092	36	23	a	a	DET
cana-6092	36	24	target	target	NOUN
cana-6092	36	25	output	output	NOUN
cana-6092	36	26	y_i	y_i	NOUN
cana-6092	36	27	and	and	CCONJ
cana-6092	36	28	other	other	ADJ
cana-6092	36	29	observed	observe	VERB
cana-6092	36	30	quantities	quantity	NOUN
cana-6092	36	31	γ_i	γ_i	ADP
cana-6092	36	32	,	,	PUNCT
cana-6092	36	33	where	where	SCONJ
cana-6092	36	34	ℒ	ℒ	PROPN
cana-6092	36	35	denotes	denote	VERB
cana-6092	36	36	the	the	DET
cana-6092	36	37	error	error	NOUN
cana-6092	36	38	metric	metric	NOUN
cana-6092	36	39	and	and	CCONJ
cana-6092	36	40	f	f	PROPN
cana-6092	36	41	represents	represent	VERB
cana-6092	36	42	the	the	DET
cana-6092	36	43	differentiable	differentiable	ADJ
cana-6092	36	44	forward	forward	ADJ
cana-6092	36	45	process	process	NOUN
cana-6092	36	46	3	3	NUM
cana-6092	36	47	.	.	PUNCT
cana-6092	37	1	the	the	DET
cana-6092	37	2	fundamental	fundamental	ADJ
cana-6092	37	3	advantage	advantage	NOUN
cana-6092	37	4	of	of	ADP
cana-6092	37	5	neural	neural	ADJ
cana-6092	37	6	networks	network	NOUN
cana-6092	37	7	lies	lie	VERB
cana-6092	37	8	in	in	ADP
cana-6092	37	9	their	their	PRON
cana-6092	37	10	universal	universal	ADJ
cana-6092	37	11	approximation	approximation	NOUN
cana-6092	37	12	capability	capability	NOUN
cana-6092	37	13	,	,	PUNCT
cana-6092	37	14	enabling	enable	VERB
cana-6092	37	15	them	they	PRON
cana-6092	37	16	to	to	PART
cana-6092	37	17	represent	represent	VERB
cana-6092	37	18	complex	complex	ADJ
cana-6092	37	19	nonlinear	nonlinear	ADJ
cana-6092	37	20	mappings	mapping	NOUN
cana-6092	37	21	between	between	ADP
cana-6092	37	22	high	high	ADJ
cana-6092	37	23	-	-	PUNCT
cana-6092	37	24	dimensional	dimensional	ADJ
cana-6092	37	25	spaces	space	NOUN
cana-6092	37	26	4	4	NUM
cana-6092	37	27	.	.	X
cana-6092	37	28	for	for	ADP
cana-6092	37	29	inverse	inverse	NOUN
cana-6092	37	30	problems	problem	NOUN
cana-6092	37	31	,	,	PUNCT
cana-6092	37	32	this	this	PRON
cana-6092	37	33	means	mean	VERB
cana-6092	37	34	networks	network	NOUN
cana-6092	37	35	can	can	AUX
cana-6092	37	36	learn	learn	VERB
cana-6092	37	37	to	to	PART
cana-6092	37	38	map	map	VERB
cana-6092	37	39	from	from	ADP
cana-6092	37	40	the	the	DET
cana-6092	37	41	measurement	measurement	NOUN
cana-6092	37	42	space	space	NOUN
cana-6092	37	43	to	to	ADP
cana-6092	37	44	the	the	DET
cana-6092	37	45	parameter	parameter	NOUN
cana-6092	37	46	space	space	NOUN
cana-6092	37	47	while	while	SCONJ
cana-6092	37	48	incorporating	incorporate	VERB
cana-6092	37	49	sophisticated	sophisticated	ADJ
cana-6092	37	50	prior	prior	ADJ
cana-6092	37	51	information	information	NOUN
cana-6092	37	52	learned	learn	VERB
cana-6092	37	53	from	from	ADP
cana-6092	37	54	data	datum	NOUN
cana-6092	37	55	rather	rather	ADV
cana-6092	37	56	than	than	ADP
cana-6092	37	57	explicitly	explicitly	ADV
cana-6092	37	58	specified	specify	VERB
cana-6092	37	59	through	through	ADP
cana-6092	37	60	regularizers	regularizer	NOUN
cana-6092	37	61	.	.	PUNCT
cana-6092	38	1	aspect	aspect	VERB
cana-6092	38	2	traditional	traditional	ADJ
cana-6092	38	3	methods	method	NOUN
cana-6092	38	4	neural	neural	ADJ
cana-6092	38	5	network	network	NOUN
cana-6092	38	6	approaches	approach	VERB
cana-6092	38	7	prior	prior	ADJ
cana-6092	38	8	representation	representation	NOUN
cana-6092	38	9	explicit	explicit	ADJ
cana-6092	38	10	analytical	analytical	ADJ
cana-6092	38	11	forms	form	NOUN
cana-6092	38	12	(	(	PUNCT
cana-6092	38	13	e.g.	e.g.	ADV
cana-6092	38	14	,	,	PUNCT
cana-6092	38	15	smoothness	smoothness	ADJ
cana-6092	38	16	,	,	PUNCT
cana-6092	38	17	sparsity	sparsity	NOUN
cana-6092	38	18	)	)	PUNCT
cana-6092	38	19	implicitly	implicitly	ADV
cana-6092	38	20	learned	learn	VERB
cana-6092	38	21	from	from	ADP
cana-6092	38	22	data	data	NOUN
cana-6092	38	23	computational	computational	ADJ
cana-6092	38	24	cost	cost	NOUN
cana-6092	38	25	high	high	ADJ
cana-6092	38	26	(	(	PUNCT
cana-6092	38	27	iterative	iterative	NOUN
cana-6092	38	28	optimization	optimization	NOUN
cana-6092	38	29	)	)	PUNCT
cana-6092	38	30	low	low	ADV
cana-6092	38	31	after	after	SCONJ
cana-6092	38	32	training	training	NOUN
cana-6092	38	33	(	(	PUNCT
cana-6092	38	34	forward	forward	ADV
cana-6092	38	35	pass	pass	NOUN
cana-6092	38	36	)	)	PUNCT
cana-6092	38	37	handling	handle	VERB
cana-6092	38	38	complex	complex	ADJ
cana-6092	38	39	priors	prior	NOUN
cana-6092	38	40	limited	limit	VERB
cana-6092	38	41	to	to	ADP
cana-6092	38	42	designed	design	VERB
cana-6092	38	43	regularizers	regularizer	NOUN
cana-6092	38	44	can	can	AUX
cana-6092	38	45	capture	capture	VERB
cana-6092	39	1	complex	complex	ADJ
cana-6092	39	2	,	,	PUNCT
cana-6092	39	3	multi	multi	ADJ
cana-6092	39	4	-	-	ADJ
cana-6092	39	5	modal	modal	ADJ
cana-6092	39	6	distributions	distribution	NOUN
cana-6092	39	7	theoretical	theoretical	ADJ
cana-6092	39	8	guarantees	guarantee	NOUN
cana-6092	39	9	well	well	ADV
cana-6092	39	10	-	-	PUNCT
cana-6092	39	11	established	establish	VERB
cana-6092	39	12	theory	theory	NOUN
cana-6092	39	13	emerging	emerge	VERB
cana-6092	39	14	theoretical	theoretical	ADJ
cana-6092	39	15	understanding	understanding	NOUN
cana-6092	39	16	adaptability	adaptability	NOUN
cana-6092	39	17	to	to	ADP
cana-6092	39	18	new	new	ADJ
cana-6092	39	19	data	datum	NOUN
cana-6092	39	20	requires	require	VERB
cana-6092	39	21	re	re	NOUN
cana-6092	39	22	-	-	NOUN
cana-6092	39	23	optimization	optimization	NOUN
cana-6092	39	24	generalizes	generalize	VERB
cana-6092	39	25	to	to	ADP
cana-6092	39	26	similar	similar	ADJ
cana-6092	39	27	problems	problem	NOUN
cana-6092	39	28	uncertainty	uncertainty	NOUN
cana-6092	39	29	quantification	quantification	NOUN
cana-6092	39	30	challenging	challenging	ADJ
cana-6092	39	31	,	,	PUNCT
cana-6092	39	32	often	often	ADV
cana-6092	39	33	limited	limit	VERB
cana-6092	39	34	possible	possible	ADJ
cana-6092	39	35	through	through	SCONJ
cana-6092	39	36	bayesian	bayesian	NOUN
cana-6092	39	37	frameworks	framework	NOUN
cana-6092	39	38	table	table	VERB
cana-6092	39	39	1	1	NUM
cana-6092	39	40	:	:	PUNCT
cana-6092	39	41	comparison	comparison	NOUN
cana-6092	39	42	of	of	ADP
cana-6092	39	43	traditional	traditional	ADJ
cana-6092	39	44	and	and	CCONJ
cana-6092	39	45	neural	neural	ADJ
cana-6092	39	46	network	network	NOUN
cana-6092	39	47	approaches	approach	NOUN
cana-6092	39	48	to	to	ADP
cana-6092	39	49	inverse	inverse	NOUN
cana-6092	39	50	problems	problem	NOUN
cana-6092	39	51	2.3	2.3	NUM
cana-6092	39	52	stability	stability	NOUN
cana-6092	39	53	-	-	PUNCT
cana-6092	39	54	accuracy	accuracy	NOUN
cana-6092	39	55	trade	trade	NOUN
cana-6092	39	56	-	-	PUNCT
cana-6092	39	57	offs	off	VERB
cana-6092	39	58	a	a	DET
cana-6092	39	59	critical	critical	ADJ
cana-6092	39	60	theoretical	theoretical	ADJ
cana-6092	39	61	consideration	consideration	NOUN
cana-6092	39	62	for	for	ADP
cana-6092	39	63	neural	neural	ADJ
cana-6092	39	64	networks	network	NOUN
cana-6092	39	65	in	in	ADP
cana-6092	39	66	inverse	inverse	NOUN
cana-6092	39	67	problems	problem	NOUN
cana-6092	39	68	is	be	AUX
cana-6092	39	69	the	the	DET
cana-6092	39	70	stability	stability	NOUN
cana-6092	39	71	-	-	PUNCT
cana-6092	39	72	accuracy	accuracy	NOUN
cana-6092	39	73	trade	trade	NOUN
cana-6092	39	74	-	-	PUNCT
cana-6092	39	75	off	off	NOUN
cana-6092	39	76	.	.	PUNCT
cana-6092	40	1	while	while	SCONJ
cana-6092	40	2	deep	deep	ADJ
cana-6092	40	3	learning	learning	NOUN
cana-6092	40	4	approaches	approach	NOUN
cana-6092	40	5	often	often	ADV
cana-6092	40	6	outperform	outperform	VERB
cana-6092	40	7	traditional	traditional	ADJ
cana-6092	40	8	methods	method	NOUN
cana-6092	40	9	in	in	ADP
cana-6092	40	10	terms	term	NOUN
cana-6092	40	11	of	of	ADP
cana-6092	40	12	accuracy	accuracy	NOUN
cana-6092	40	13	,	,	PUNCT
cana-6092	40	14	they	they	PRON
cana-6092	40	15	may	may	AUX
cana-6092	40	16	suffer	suffer	VERB
cana-6092	40	17	from	from	ADP
cana-6092	40	18	instability	instability	NOUN
cana-6092	40	19	with	with	ADP
cana-6092	40	20	respect	respect	NOUN
cana-6092	40	21	to	to	ADP
cana-6092	40	22	data	datum	NOUN
cana-6092	40	23	perturbation	perturbation	NOUN
cana-6092	40	24	1	1	NUM
cana-6092	40	25	.	.	PUNCT
cana-6092	41	1	evangelista	evangelista	PROPN
cana-6092	41	2	et	et	PROPN
cana-6092	41	3	al	al	PROPN
cana-6092	41	4	.	.	PROPN
cana-6092	41	5	theoretically	theoretically	ADV
cana-6092	41	6	analyze	analyze	VERB
cana-6092	41	7	this	this	DET
cana-6092	41	8	trade	trade	NOUN
cana-6092	41	9	-	-	PUNCT
cana-6092	41	10	off	off	NOUN
cana-6092	41	11	for	for	ADP
cana-6092	41	12	neural	neural	ADJ
cana-6092	41	13	networks	network	NOUN
cana-6092	41	14	solving	solve	VERB
cana-6092	41	15	linear	linear	ADJ
cana-6092	41	16	imaging	imaging	ADJ
cana-6092	41	17	inverse	inverse	NOUN
cana-6092	41	18	problems	problem	NOUN
cana-6092	41	19	,	,	PUNCT
cana-6092	41	20	showing	show	VERB
cana-6092	41	21	that	that	SCONJ
cana-6092	41	22	while	while	SCONJ
cana-6092	41	23	these	these	DET
cana-6092	41	24	algorithms	algorithm	NOUN
cana-6092	41	25	overwhelm	overwhelm	VERB
cana-6092	41	26	traditional	traditional	ADJ
cana-6092	41	27	model	model	NOUN
cana-6092	41	28	-	-	PUNCT
cana-6092	41	29	based	base	VERB
cana-6092	41	30	approaches	approach	NOUN
cana-6092	41	31	in	in	ADP
cana-6092	41	32	performance	performance	NOUN
cana-6092	41	33	,	,	PUNCT
cana-6092	41	34	they	they	PRON
cana-6092	41	35	typically	typically	ADV
cana-6092	41	36	exhibit	exhibit	VERB
cana-6092	41	37	sensitivity	sensitivity	NOUN
cana-6092	41	38	to	to	PART
cana-6092	41	39	noise	noise	VERB
cana-6092	41	40	and	and	CCONJ
cana-6092	41	41	perturbations	perturbation	NOUN
cana-6092	41	42	1	1	NUM
cana-6092	41	43	.	.	PUNCT
cana-6092	42	1	theoretical	theoretical	ADJ
cana-6092	42	2	analysis	analysis	NOUN
cana-6092	42	3	suggests	suggest	VERB
cana-6092	42	4	that	that	SCONJ
cana-6092	42	5	the	the	DET
cana-6092	42	6	loss	loss	NOUN
cana-6092	42	7	landscape	landscape	NOUN
cana-6092	42	8	l_i(x	l_i(x	NOUN
cana-6092	42	9	)	)	PUNCT
cana-6092	42	10	for	for	ADP
cana-6092	42	11	inverse	inverse	NOUN
cana-6092	42	12	problems	problem	NOUN
cana-6092	42	13	can	can	AUX
cana-6092	42	14	be	be	AUX
cana-6092	42	15	decomposed	decompose	VERB
cana-6092	42	16	into	into	ADP
cana-6092	42	17	signal	signal	NOUN
cana-6092	42	18	and	and	CCONJ
cana-6092	42	19	noise	noise	NOUN
cana-6092	42	20	components	component	NOUN
cana-6092	42	21	:	:	PUNCT
cana-6092	42	22	l_i(x	l_i(x	X
cana-6092	42	23	)	)	PUNCT
cana-6092	42	24	=	=	PUNCT
cana-6092	43	1	λ_i|x_i	λ_i|x_i	PUNCT
cana-6092	43	2	x_i^|	x_i^|	NOUN
cana-6092	44	1	+	+	NUM
cana-6092	44	2	σ_{j=1}^m	σ_{j=1}^m	ADJ
cana-6092	44	3	-a_{ij}cos(ω_{ij}x	-a_{ij}cos(ω_{ij}x	NOUN
cana-6092	44	4	+	+	CCONJ
cana-6092	44	5	φ_{ij	φ_{ij	NOUN
cana-6092	44	6	}	}	PUNCT
cana-6092	44	7	)	)	PUNCT
cana-6092	44	8	where	where	SCONJ
cana-6092	44	9	the	the	DET
cana-6092	44	10	first	first	ADJ
cana-6092	44	11	term	term	NOUN
cana-6092	44	12	represents	represent	VERB
cana-6092	44	13	the	the	DET
cana-6092	44	14	signal	signal	ADJ
cana-6092	44	15	component	component	NOUN
cana-6092	44	16	pointing	pointing	NOUN
cana-6092	44	17	toward	toward	ADP
cana-6092	44	18	desirable	desirable	ADJ
cana-6092	44	19	solutions	solution	NOUN
cana-6092	44	20	,	,	PUNCT
cana-6092	44	21	and	and	CCONJ
cana-6092	44	22	the	the	DET
cana-6092	44	23	second	second	ADJ
cana-6092	44	24	term	term	NOUN
cana-6092	44	25	represents	represent	VERB
cana-6092	44	26	noise	noise	NOUN
cana-6092	44	27	introducing	introduce	VERB
cana-6092	44	28	unwanted	unwanted	ADJ
cana-6092	44	29	features	feature	NOUN
cana-6092	44	30	like	like	ADP
cana-6092	44	31	local	local	ADJ
cana-6092	44	32	minima	minima	NOUN
cana-6092	44	33	and	and	CCONJ
cana-6092	44	34	chaotic	chaotic	ADJ
cana-6092	44	35	behavior	behavior	NOUN
cana-6092	44	36	3	3	X
cana-6092	44	37	.	.	NOUN
cana-6092	44	38	neural	neural	ADJ
cana-6092	44	39	networks	network	NOUN
cana-6092	44	40	trained	train	VERB
cana-6092	44	41	on	on	ADP
cana-6092	44	42	multiple	multiple	ADJ
cana-6092	44	43	inverse	inverse	NOUN
cana-6092	44	44	problems	problem	NOUN
cana-6092	44	45	can	can	AUX
cana-6092	44	46	effectively	effectively	ADV
cana-6092	44	47	average	average	VERB
cana-6092	44	48	out	out	ADP
cana-6092	44	49	the	the	DET
cana-6092	44	50	noise	noise	NOUN
cana-6092	44	51	components	component	NOUN
cana-6092	44	52	,	,	PUNCT
cana-6092	44	53	leading	lead	VERB
cana-6092	44	54	to	to	ADP
cana-6092	44	55	more	more	ADV
cana-6092	44	56	robust	robust	ADJ
cana-6092	44	57	optimization	optimization	NOUN
cana-6092	44	58	landscapes	landscape	NOUN
cana-6092	44	59	3	3	NUM
cana-6092	44	60	.	.	X
cana-6092	44	61	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	PROPN
cana-6092	44	62	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	44	63	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	44	64	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	44	65	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	44	66	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	44	67	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	44	68	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	44	69	communications	communication	NOUN
cana-6092	44	70	on	on	ADP
cana-6092	44	71	applied	apply	VERB
cana-6092	44	72	nonlinear	nonlinear	ADJ
cana-6092	44	73	analysis	analysis	NOUN
cana-6092	44	74	issn	issn	NOUN
cana-6092	44	75	:	:	PUNCT
cana-6092	44	76	1074	1074	NUM
cana-6092	44	77	-	-	PUNCT
cana-6092	44	78	133x	133x	NUM
cana-6092	44	79	vol	vol	NOUN
cana-6092	44	80	31	31	NUM
cana-6092	44	81	no	no	NOUN
cana-6092	44	82	.	.	NOUN
cana-6092	44	83	2	2	NUM
cana-6092	44	84	(	(	PUNCT
cana-6092	44	85	2024	2024	NUM
cana-6092	44	86	)	)	PUNCT
cana-6092	44	87	502	502	NUM
cana-6092	44	88	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	44	89	3.methodological	3.methodological	NUM
cana-6092	44	90	framework	framework	NOUN
cana-6092	44	91	3.1	3.1	NUM
cana-6092	44	92	neural	neural	ADJ
cana-6092	44	93	network	network	NOUN
cana-6092	44	94	architectures	architecture	VERB
cana-6092	44	95	the	the	DET
cana-6092	44	96	proposed	propose	VERB
cana-6092	44	97	framework	framework	NOUN
cana-6092	44	98	incorporates	incorporate	VERB
cana-6092	44	99	several	several	ADJ
cana-6092	44	100	neural	neural	ADJ
cana-6092	44	101	network	network	NOUN
cana-6092	44	102	architectures	architecture	NOUN
cana-6092	44	103	tailored	tailor	VERB
cana-6092	44	104	to	to	ADP
cana-6092	44	105	different	different	ADJ
cana-6092	44	106	aspects	aspect	NOUN
cana-6092	44	107	of	of	ADP
cana-6092	44	108	largescale	largescale	ADJ
cana-6092	44	109	inverse	inverse	NOUN
cana-6092	44	110	problems	problem	NOUN
cana-6092	44	111	:	:	PUNCT
cana-6092	44	112	physics	physics	NOUN
cana-6092	44	113	-	-	PUNCT
cana-6092	44	114	informed	inform	VERB
cana-6092	44	115	neural	neural	ADJ
cana-6092	44	116	networks	network	NOUN
cana-6092	44	117	(	(	PUNCT
cana-6092	44	118	pinns	pinns	ADJ
cana-6092	44	119	)	)	PUNCT
cana-6092	44	120	integrate	integrate	VERB
cana-6092	44	121	physical	physical	ADJ
cana-6092	44	122	principles	principle	NOUN
cana-6092	44	123	directly	directly	ADV
cana-6092	44	124	into	into	ADP
cana-6092	44	125	the	the	DET
cana-6092	44	126	learning	learning	NOUN
cana-6092	44	127	process	process	NOUN
cana-6092	44	128	by	by	ADP
cana-6092	44	129	incorporating	incorporate	VERB
cana-6092	44	130	the	the	DET
cana-6092	44	131	governing	govern	VERB
cana-6092	44	132	equations	equation	NOUN
cana-6092	44	133	into	into	ADP
cana-6092	44	134	the	the	DET
cana-6092	44	135	loss	loss	NOUN
cana-6092	44	136	function	function	NOUN
cana-6092	44	137	47	47	NUM
cana-6092	44	138	.	.	PUNCT
cana-6092	45	1	for	for	ADP
cana-6092	45	2	inverse	inverse	NOUN
cana-6092	45	3	problems	problem	NOUN
cana-6092	45	4	,	,	PUNCT
cana-6092	45	5	pinns	pinns	ADV
cana-6092	45	6	can	can	AUX
cana-6092	45	7	simultaneously	simultaneously	ADV
cana-6092	45	8	estimate	estimate	VERB
cana-6092	45	9	parameters	parameter	NOUN
cana-6092	45	10	and	and	CCONJ
cana-6092	45	11	solutions	solution	NOUN
cana-6092	45	12	by	by	ADP
cana-6092	45	13	minimizing	minimize	VERB
cana-6092	45	14	a	a	DET
cana-6092	45	15	composite	composite	ADJ
cana-6092	45	16	loss	loss	NOUN
cana-6092	45	17	function	function	NOUN
cana-6092	45	18	that	that	PRON
cana-6092	45	19	includes	include	VERB
cana-6092	45	20	data	datum	NOUN
cana-6092	45	21	fidelity	fidelity	PROPN
cana-6092	45	22	terms	term	NOUN
cana-6092	45	23	,	,	PUNCT
cana-6092	45	24	physical	physical	ADJ
cana-6092	45	25	consistency	consistency	NOUN
cana-6092	45	26	terms	term	NOUN
cana-6092	45	27	,	,	PUNCT
cana-6092	45	28	and	and	CCONJ
cana-6092	45	29	boundary	boundary	ADJ
cana-6092	45	30	/	/	SYM
cana-6092	45	31	initial	initial	ADJ
cana-6092	45	32	condition	condition	NOUN
cana-6092	45	33	terms	term	NOUN
cana-6092	45	34	4	4	NUM
cana-6092	45	35	.	.	PUNCT
cana-6092	46	1	the	the	DET
cana-6092	46	2	architecture	architecture	NOUN
cana-6092	46	3	typically	typically	ADV
cana-6092	46	4	consists	consist	VERB
cana-6092	46	5	of	of	ADP
cana-6092	46	6	fully	fully	ADV
cana-6092	46	7	connected	connect	VERB
cana-6092	46	8	networks	network	NOUN
cana-6092	46	9	with	with	ADP
cana-6092	46	10	nonlinear	nonlinear	ADJ
cana-6092	46	11	activation	activation	NOUN
cana-6092	46	12	functions	function	NOUN
cana-6092	46	13	chosen	choose	VERB
cana-6092	46	14	based	base	VERB
cana-6092	46	15	on	on	ADP
cana-6092	46	16	the	the	DET
cana-6092	46	17	specific	specific	ADJ
cana-6092	46	18	differential	differential	ADJ
cana-6092	46	19	equations	equation	NOUN
cana-6092	46	20	involved	involve	VERB
cana-6092	46	21	4	4	NUM
cana-6092	46	22	.	.	PUNCT
cana-6092	46	23	generative	generative	ADJ
cana-6092	46	24	adversarial	adversarial	ADJ
cana-6092	46	25	networks	network	NOUN
cana-6092	46	26	(	(	PUNCT
cana-6092	46	27	gans	gan	NOUN
cana-6092	46	28	)	)	PUNCT
cana-6092	46	29	learn	learn	VERB
cana-6092	46	30	to	to	PART
cana-6092	46	31	generate	generate	VERB
cana-6092	46	32	solutions	solution	NOUN
cana-6092	46	33	that	that	PRON
cana-6092	46	34	are	be	AUX
cana-6092	46	35	statistically	statistically	ADV
cana-6092	46	36	similar	similar	ADJ
cana-6092	46	37	to	to	ADP
cana-6092	46	38	training	train	VERB
cana-6092	46	39	data	datum	NOUN
cana-6092	46	40	while	while	SCONJ
cana-6092	46	41	consistent	consistent	ADJ
cana-6092	46	42	with	with	ADP
cana-6092	46	43	measurements	measurement	NOUN
cana-6092	46	44	3	3	NUM
cana-6092	46	45	.	.	PUNCT
cana-6092	47	1	conditional	conditional	ADJ
cana-6092	47	2	gans	gan	NOUN
cana-6092	47	3	are	be	AUX
cana-6092	47	4	particularly	particularly	ADV
cana-6092	47	5	effective	effective	ADJ
cana-6092	47	6	for	for	ADP
cana-6092	47	7	inverse	inverse	NOUN
cana-6092	47	8	problems	problem	NOUN
cana-6092	47	9	,	,	PUNCT
cana-6092	47	10	as	as	SCONJ
cana-6092	47	11	they	they	PRON
cana-6092	47	12	can	can	AUX
cana-6092	47	13	generate	generate	VERB
cana-6092	47	14	samples	sample	NOUN
cana-6092	47	15	conditioned	condition	VERB
cana-6092	47	16	on	on	ADP
cana-6092	47	17	measurement	measurement	NOUN
cana-6092	47	18	data	datum	NOUN
cana-6092	47	19	.	.	PUNCT
cana-6092	48	1	the	the	DET
cana-6092	48	2	framework	framework	NOUN
cana-6092	48	3	incorporates	incorporate	VERB
cana-6092	48	4	wasserstein	wasserstein	NOUN
cana-6092	48	5	gans	gan	NOUN
cana-6092	48	6	with	with	ADP
cana-6092	48	7	gradient	gradient	ADJ
cana-6092	48	8	penalty	penalty	NOUN
cana-6092	48	9	(	(	PUNCT
cana-6092	48	10	wgan	wgan	VERB
cana-6092	48	11	-	-	PUNCT
cana-6092	48	12	gp	gp	NOUN
cana-6092	48	13	)	)	PUNCT
cana-6092	48	14	to	to	PART
cana-6092	48	15	improve	improve	VERB
cana-6092	48	16	training	train	VERB
cana-6092	48	17	stability	stability	NOUN
cana-6092	48	18	and	and	CCONJ
cana-6092	48	19	convergence	convergence	NOUN
cana-6092	48	20	3	3	NUM
cana-6092	48	21	.	.	PUNCT
cana-6092	48	22	differentiable	differentiable	ADJ
cana-6092	48	23	simulation	simulation	NOUN
cana-6092	48	24	networks	network	NOUN
cana-6092	48	25	enable	enable	VERB
cana-6092	48	26	end	end	NOUN
cana-6092	48	27	-	-	PUNCT
cana-6092	48	28	to	to	ADP
cana-6092	48	29	-	-	PUNCT
cana-6092	48	30	end	end	NOUN
cana-6092	48	31	training	training	NOUN
cana-6092	48	32	by	by	ADP
cana-6092	48	33	incorporating	incorporate	VERB
cana-6092	48	34	differentiable	differentiable	ADJ
cana-6092	48	35	approximations	approximation	NOUN
cana-6092	48	36	of	of	ADP
cana-6092	48	37	physical	physical	ADJ
cana-6092	48	38	processes	process	NOUN
cana-6092	48	39	23	23	NUM
cana-6092	48	40	.	.	PUNCT
cana-6092	49	1	these	these	DET
cana-6092	49	2	networks	network	NOUN
cana-6092	49	3	allow	allow	VERB
cana-6092	49	4	backpropagation	backpropagation	NOUN
cana-6092	49	5	of	of	ADP
cana-6092	49	6	gradients	gradient	NOUN
cana-6092	49	7	through	through	ADP
cana-6092	49	8	the	the	DET
cana-6092	49	9	forward	forward	ADJ
cana-6092	49	10	process	process	NOUN
cana-6092	49	11	,	,	PUNCT
cana-6092	49	12	facilitating	facilitate	VERB
cana-6092	49	13	learning	learning	NOUN
cana-6092	49	14	of	of	ADP
cana-6092	49	15	inverse	inverse	ADJ
cana-6092	49	16	mappings	mapping	NOUN
cana-6092	49	17	that	that	PRON
cana-6092	49	18	respect	respect	VERB
cana-6092	49	19	physical	physical	ADJ
cana-6092	49	20	constraints	constraint	NOUN
cana-6092	49	21	.	.	PUNCT
cana-6092	50	1	this	this	DET
cana-6092	50	2	approach	approach	NOUN
cana-6092	50	3	is	be	AUX
cana-6092	50	4	particularly	particularly	ADV
cana-6092	50	5	valuable	valuable	ADJ
cana-6092	50	6	for	for	ADP
cana-6092	50	7	problems	problem	NOUN
cana-6092	50	8	where	where	SCONJ
cana-6092	50	9	the	the	DET
cana-6092	50	10	forward	forward	ADJ
cana-6092	50	11	model	model	NOUN
cana-6092	50	12	is	be	AUX
cana-6092	50	13	known	know	VERB
cana-6092	50	14	but	but	CCONJ
cana-6092	50	15	computationally	computationally	ADV
cana-6092	50	16	expensive	expensive	ADJ
cana-6092	50	17	3	3	NUM
cana-6092	50	18	.	.	NOUN
cana-6092	50	19	3.2	3.2	NUM
cana-6092	50	20	training	training	NOUN
cana-6092	50	21	strategies	strategy	NOUN
cana-6092	50	22	the	the	DET
cana-6092	50	23	framework	framework	NOUN
cana-6092	50	24	employs	employ	VERB
cana-6092	50	25	specialized	specialized	ADJ
cana-6092	50	26	training	training	NOUN
cana-6092	50	27	strategies	strategy	NOUN
cana-6092	50	28	to	to	PART
cana-6092	50	29	address	address	VERB
cana-6092	50	30	challenges	challenge	NOUN
cana-6092	50	31	specific	specific	ADJ
cana-6092	50	32	to	to	ADP
cana-6092	50	33	inverse	inverse	NOUN
cana-6092	50	34	problems	problem	NOUN
cana-6092	50	35	:	:	PUNCT
cana-6092	50	36	end	end	NOUN
cana-6092	50	37	-	-	PUNCT
cana-6092	50	38	to	to	ADP
cana-6092	50	39	-	-	PUNCT
cana-6092	50	40	end	end	NOUN
cana-6092	50	41	training	training	NOUN
cana-6092	50	42	leverages	leverage	NOUN
cana-6092	50	43	differentiable	differentiable	VERB
cana-6092	50	44	forward	forward	ADJ
cana-6092	50	45	models	model	NOUN
cana-6092	50	46	to	to	PART
cana-6092	50	47	backpropagate	backpropagate	VERB
cana-6092	50	48	gradients	gradient	NOUN
cana-6092	50	49	from	from	ADP
cana-6092	50	50	the	the	DET
cana-6092	50	51	output	output	NOUN
cana-6092	50	52	directly	directly	ADV
cana-6092	50	53	to	to	ADP
cana-6092	50	54	the	the	DET
cana-6092	50	55	network	network	NOUN
cana-6092	50	56	weights	weight	NOUN
cana-6092	50	57	,	,	PUNCT
cana-6092	50	58	minimizing	minimize	VERB
cana-6092	50	59	the	the	DET
cana-6092	50	60	difference	difference	NOUN
cana-6092	50	61	between	between	ADP
cana-6092	50	62	target	target	NOUN
cana-6092	50	63	output	output	NOUN
cana-6092	50	64	and	and	CCONJ
cana-6092	50	65	the	the	DET
cana-6092	50	66	output	output	NOUN
cana-6092	50	67	resulting	result	VERB
cana-6092	50	68	from	from	ADP
cana-6092	50	69	predicted	predict	VERB
cana-6092	50	70	solutions	solution	NOUN
cana-6092	50	71	3	3	X
cana-6092	50	72	.	.	PUNCT
cana-6092	51	1	this	this	DET
cana-6092	51	2	approach	approach	NOUN
cana-6092	51	3	avoids	avoid	VERB
cana-6092	51	4	the	the	DET
cana-6092	51	5	need	need	NOUN
cana-6092	51	6	for	for	ADP
cana-6092	51	7	precomputed	precompute	VERB
cana-6092	51	8	solutions	solution	NOUN
cana-6092	51	9	as	as	ADP
cana-6092	51	10	labels	label	NOUN
cana-6092	51	11	and	and	CCONJ
cana-6092	51	12	effectively	effectively	ADV
cana-6092	51	13	minimizes	minimize	VERB
cana-6092	51	14	the	the	DET
cana-6092	51	15	actual	actual	ADJ
cana-6092	51	16	error	error	NOUN
cana-6092	51	17	metric	metric	NOUN
cana-6092	51	18	rather	rather	ADV
cana-6092	51	19	than	than	ADP
cana-6092	51	20	distance	distance	NOUN
cana-6092	51	21	to	to	ADP
cana-6092	51	22	individual	individual	ADJ
cana-6092	51	23	solutions	solution	NOUN
cana-6092	51	24	3	3	X
cana-6092	51	25	.	.	X
cana-6092	51	26	curriculum	curriculum	NOUN
cana-6092	51	27	learning	learn	VERB
cana-6092	51	28	progressively	progressively	ADV
cana-6092	51	29	increases	increase	VERB
cana-6092	51	30	problem	problem	NOUN
cana-6092	51	31	complexity	complexity	NOUN
cana-6092	51	32	during	during	ADP
cana-6092	51	33	training	training	NOUN
cana-6092	51	34	,	,	PUNCT
cana-6092	51	35	starting	start	VERB
cana-6092	51	36	with	with	ADP
cana-6092	51	37	simpler	simple	ADJ
cana-6092	51	38	instances	instance	NOUN
cana-6092	51	39	and	and	CCONJ
cana-6092	51	40	gradually	gradually	ADV
cana-6092	51	41	introducing	introduce	VERB
cana-6092	51	42	more	more	ADV
cana-6092	51	43	challenging	challenging	ADJ
cana-6092	51	44	cases	case	NOUN
cana-6092	51	45	.	.	PUNCT
cana-6092	52	1	this	this	DET
cana-6092	52	2	approach	approach	NOUN
cana-6092	52	3	improves	improve	VERB
cana-6092	52	4	convergence	convergence	NOUN
cana-6092	52	5	and	and	CCONJ
cana-6092	52	6	generalization	generalization	NOUN
cana-6092	52	7	for	for	ADP
cana-6092	52	8	problems	problem	NOUN
cana-6092	52	9	with	with	ADP
cana-6092	52	10	complex	complex	ADJ
cana-6092	52	11	landscapes	landscape	NOUN
cana-6092	52	12	or	or	CCONJ
cana-6092	52	13	multiple	multiple	ADJ
cana-6092	52	14	local	local	ADJ
cana-6092	52	15	minima	minima	NOUN
cana-6092	52	16	3	3	X
cana-6092	52	17	.	.	PUNCT
cana-6092	52	18	multi	multi	ADJ
cana-6092	52	19	-	-	NOUN
cana-6092	52	20	task	task	ADJ
cana-6092	52	21	learning	learning	NOUN
cana-6092	52	22	simultaneously	simultaneously	ADV
cana-6092	52	23	addresses	address	NOUN
cana-6092	52	24	related	related	ADJ
cana-6092	52	25	inverse	inverse	NOUN
cana-6092	52	26	problems	problem	NOUN
cana-6092	52	27	,	,	PUNCT
cana-6092	52	28	sharing	share	VERB
cana-6092	52	29	representations	representation	NOUN
cana-6092	52	30	across	across	ADP
cana-6092	52	31	tasks	task	NOUN
cana-6092	52	32	to	to	PART
cana-6092	52	33	improve	improve	VERB
cana-6092	52	34	data	data	NOUN
cana-6092	52	35	efficiency	efficiency	NOUN
cana-6092	52	36	and	and	CCONJ
cana-6092	52	37	generalization	generalization	NOUN
cana-6092	52	38	.	.	PUNCT
cana-6092	53	1	this	this	DET
cana-6092	53	2	approach	approach	NOUN
cana-6092	53	3	is	be	AUX
cana-6092	53	4	particularly	particularly	ADV
cana-6092	53	5	valuable	valuable	ADJ
cana-6092	53	6	for	for	ADP
cana-6092	53	7	problems	problem	NOUN
cana-6092	53	8	with	with	ADP
cana-6092	53	9	limited	limited	ADJ
cana-6092	53	10	training	training	NOUN
cana-6092	53	11	data	datum	NOUN
cana-6092	53	12	or	or	CCONJ
cana-6092	53	13	varied	varied	ADJ
cana-6092	53	14	measurement	measurement	NOUN
cana-6092	53	15	scenarios	scenario	NOUN
cana-6092	53	16	3	3	NUM
cana-6092	53	17	.	.	NOUN
cana-6092	53	18	problem	problem	NOUN
cana-6092	53	19	type	type	NOUN
cana-6092	53	20	recommended	recommend	VERB
cana-6092	53	21	architecture	architecture	NOUN
cana-6092	53	22	key	key	ADJ
cana-6092	53	23	features	feature	NOUN
cana-6092	53	24	application	application	NOUN
cana-6092	53	25	examples	example	NOUN
cana-6092	53	26	linear	linear	ADJ
cana-6092	53	27	imaging	imaging	NOUN
cana-6092	53	28	problems	problem	NOUN
cana-6092	53	29	convolutional	convolutional	ADJ
cana-6092	53	30	encoderdecoder	encoderdecoder	NOUN
cana-6092	53	31	leverages	leverage	NOUN
cana-6092	53	32	spatial	spatial	ADJ
cana-6092	53	33	correlations	correlation	NOUN
cana-6092	53	34	,	,	PUNCT
cana-6092	53	35	translation	translation	NOUN
cana-6092	53	36	invariance	invariance	NOUN
cana-6092	53	37	image	image	NOUN
cana-6092	53	38	deblurring	deblurring	NOUN
cana-6092	53	39	,	,	PUNCT
cana-6092	53	40	tomography	tomography	NOUN
cana-6092	53	41	1	1	NUM
cana-6092	53	42	nonlinear	nonlinear	ADJ
cana-6092	53	43	pde	pde	NOUN
cana-6092	53	44	-	-	PUNCT
cana-6092	53	45	based	base	VERB
cana-6092	53	46	problems	problem	NOUN
cana-6092	53	47	physics	physics	NOUN
cana-6092	53	48	-	-	PUNCT
cana-6092	53	49	informed	inform	VERB
cana-6092	53	50	neural	neural	ADJ
cana-6092	53	51	networks	network	NOUN
cana-6092	53	52	incorporates	incorporate	VERB
cana-6092	53	53	physical	physical	ADJ
cana-6092	53	54	constraints	constraint	NOUN
cana-6092	53	55	,	,	PUNCT
cana-6092	53	56	handles	handle	VERB
cana-6092	53	57	complex	complex	ADJ
cana-6092	53	58	geometries	geometry	NOUN
cana-6092	53	59	heat	heat	NOUN
cana-6092	53	60	equation	equation	NOUN
cana-6092	53	61	,	,	PUNCT
cana-6092	53	62	wave	wave	NOUN
cana-6092	53	63	equation	equation	NOUN
cana-6092	53	64	4	4	NUM
cana-6092	53	65	high	high	ADV
cana-6092	53	66	-	-	PUNCT
cana-6092	53	67	dimensional	dimensional	ADJ
cana-6092	53	68	parameter	parameter	NOUN
cana-6092	53	69	estimation	estimation	NOUN
cana-6092	53	70	generative	generative	VERB
cana-6092	53	71	adversarial	adversarial	ADJ
cana-6092	53	72	networks	network	NOUN
cana-6092	53	73	captures	capture	VERB
cana-6092	53	74	complex	complex	ADJ
cana-6092	53	75	distributions	distribution	NOUN
cana-6092	53	76	,	,	PUNCT
cana-6092	53	77	generates	generate	VERB
cana-6092	53	78	diverse	diverse	ADJ
cana-6092	53	79	solutions	solution	NOUN
cana-6092	53	80	seismic	seismic	ADJ
cana-6092	53	81	inversion	inversion	NOUN
cana-6092	53	82	,	,	PUNCT
cana-6092	53	83	material	material	NOUN
cana-6092	53	84	design	design	NOUN
cana-6092	53	85	3	3	NUM
cana-6092	53	86	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	53	87	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	ADP
cana-6092	53	88	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	53	89	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	53	90	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	53	91	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	53	92	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	PROPN
cana-6092	53	93	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	53	94	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	53	95	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	53	96	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	53	97	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	53	98	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	53	99	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	53	100	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	53	101	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	53	102	communications	communication	NOUN
cana-6092	53	103	on	on	ADP
cana-6092	53	104	applied	apply	VERB
cana-6092	53	105	nonlinear	nonlinear	ADJ
cana-6092	53	106	analysis	analysis	NOUN
cana-6092	53	107	issn	issn	NOUN
cana-6092	53	108	:	:	PUNCT
cana-6092	53	109	1074	1074	NUM
cana-6092	53	110	-	-	PUNCT
cana-6092	53	111	133x	133x	NUM
cana-6092	53	112	vol	vol	NOUN
cana-6092	53	113	31	31	NUM
cana-6092	53	114	no	no	NOUN
cana-6092	53	115	.	.	NOUN
cana-6092	53	116	2	2	NUM
cana-6092	53	117	(	(	PUNCT
cana-6092	53	118	2024	2024	NUM
cana-6092	53	119	)	)	PUNCT
cana-6092	53	120	503	503	NUM
cana-6092	53	121	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	53	122	time	time	NOUN
cana-6092	53	123	-	-	PUNCT
cana-6092	53	124	dependent	dependent	ADJ
cana-6092	53	125	problems	problem	NOUN
cana-6092	53	126	recurrent	recurrent	VERB
cana-6092	53	127	neural	neural	ADJ
cana-6092	53	128	networks	network	NOUN
cana-6092	53	129	handles	handle	VERB
cana-6092	53	130	temporal	temporal	ADJ
cana-6092	53	131	dependencies	dependency	NOUN
cana-6092	53	132	,	,	PUNCT
cana-6092	53	133	sequential	sequential	ADJ
cana-6092	53	134	data	datum	NOUN
cana-6092	53	135	dynamic	dynamic	ADJ
cana-6092	53	136	systems	system	NOUN
cana-6092	53	137	,	,	PUNCT
cana-6092	53	138	forecasting	forecast	VERB
cana-6092	53	139	4	4	NUM
cana-6092	53	140	table	table	NOUN
cana-6092	53	141	2	2	NUM
cana-6092	53	142	:	:	PUNCT
cana-6092	53	143	neural	neural	ADJ
cana-6092	53	144	network	network	NOUN
cana-6092	53	145	architectures	architecture	NOUN
cana-6092	53	146	for	for	ADP
cana-6092	53	147	different	different	ADJ
cana-6092	53	148	inverse	inverse	NOUN
cana-6092	53	149	problem	problem	NOUN
cana-6092	53	150	types	type	NOUN
cana-6092	53	151	3.3	3.3	NUM
cana-6092	53	152	incorporating	incorporate	VERB
cana-6092	53	153	physical	physical	ADJ
cana-6092	53	154	knowledge	knowledge	NOUN
cana-6092	53	155	a	a	DET
cana-6092	53	156	key	key	ADJ
cana-6092	53	157	advantage	advantage	NOUN
cana-6092	53	158	of	of	ADP
cana-6092	53	159	the	the	DET
cana-6092	53	160	proposed	propose	VERB
cana-6092	53	161	framework	framework	NOUN
cana-6092	53	162	is	be	AUX
cana-6092	53	163	its	its	PRON
cana-6092	53	164	ability	ability	NOUN
cana-6092	53	165	to	to	PART
cana-6092	53	166	incorporate	incorporate	VERB
cana-6092	53	167	physical	physical	ADJ
cana-6092	53	168	knowledge	knowledge	NOUN
cana-6092	53	169	through	through	ADP
cana-6092	53	170	various	various	ADJ
cana-6092	53	171	mechanisms	mechanism	NOUN
cana-6092	53	172	:	:	PUNCT
cana-6092	53	173	physical	physical	ADJ
cana-6092	53	174	constraints	constraint	NOUN
cana-6092	53	175	integration	integration	NOUN
cana-6092	53	176	directly	directly	ADV
cana-6092	53	177	embeds	embed	VERB
cana-6092	53	178	governing	govern	VERB
cana-6092	53	179	equations	equation	NOUN
cana-6092	53	180	,	,	PUNCT
cana-6092	53	181	boundary	boundary	ADJ
cana-6092	53	182	conditions	condition	NOUN
cana-6092	53	183	,	,	PUNCT
cana-6092	53	184	and	and	CCONJ
cana-6092	53	185	initial	initial	ADJ
cana-6092	53	186	conditions	condition	NOUN
cana-6092	53	187	into	into	ADP
cana-6092	53	188	the	the	DET
cana-6092	53	189	loss	loss	NOUN
cana-6092	53	190	function	function	NOUN
cana-6092	53	191	47	47	NUM
cana-6092	53	192	.	.	PUNCT
cana-6092	54	1	for	for	ADP
cana-6092	54	2	example	example	NOUN
cana-6092	54	3	,	,	PUNCT
cana-6092	54	4	when	when	SCONJ
cana-6092	54	5	solving	solve	VERB
cana-6092	54	6	differential	differential	ADJ
cana-6092	54	7	equations	equation	NOUN
cana-6092	54	8	,	,	PUNCT
cana-6092	54	9	the	the	DET
cana-6092	54	10	loss	loss	NOUN
cana-6092	54	11	function	function	NOUN
cana-6092	54	12	includes	include	VERB
cana-6092	54	13	terms	term	NOUN
cana-6092	54	14	that	that	PRON
cana-6092	54	15	penalize	penalize	VERB
cana-6092	54	16	violations	violation	NOUN
cana-6092	54	17	of	of	ADP
cana-6092	54	18	the	the	DET
cana-6092	54	19	pde	pde	NOUN
cana-6092	54	20	at	at	ADP
cana-6092	54	21	collocation	collocation	NOUN
cana-6092	54	22	points	point	NOUN
cana-6092	54	23	:	:	PUNCT
cana-6092	54	24	ℒ	ℒ	PROPN
cana-6092	54	25	=	=	PUNCT
cana-6092	54	26	ℒ_data	ℒ_data	PROPN
cana-6092	54	27	+	+	NOUN
cana-6092	54	28	λ_pdeℒ_pde	λ_pdeℒ_pde	PROPN
cana-6092	54	29	+	+	CCONJ
cana-6092	54	30	λ_bcℒ_bc	λ_bcℒ_bc	NOUN
cana-6092	54	31	+	+	CCONJ
cana-6092	54	32	λ_icℒ_ic	λ_icℒ_ic	NOUN
cana-6092	54	33	where	where	SCONJ
cana-6092	54	34	the	the	DET
cana-6092	54	35	terms	term	NOUN
cana-6092	54	36	represent	represent	VERB
cana-6092	54	37	data	datum	NOUN
cana-6092	54	38	fidelity	fidelity	PROPN
cana-6092	54	39	,	,	PUNCT
cana-6092	54	40	pde	pde	PROPN
cana-6092	54	41	residual	residual	ADJ
cana-6092	54	42	,	,	PUNCT
cana-6092	54	43	boundary	boundary	ADJ
cana-6092	54	44	conditions	condition	NOUN
cana-6092	54	45	,	,	PUNCT
cana-6092	54	46	and	and	CCONJ
cana-6092	54	47	initial	initial	ADJ
cana-6092	54	48	conditions	condition	NOUN
cana-6092	54	49	,	,	PUNCT
cana-6092	54	50	respectively	respectively	ADV
cana-6092	54	51	4	4	NUM
cana-6092	54	52	.	.	PUNCT
cana-6092	54	53	differentiable	differentiable	ADJ
cana-6092	54	54	physics	physics	NOUN
cana-6092	54	55	utilizes	utilize	VERB
cana-6092	54	56	automatic	automatic	ADJ
cana-6092	54	57	differentiation	differentiation	NOUN
cana-6092	54	58	to	to	PART
cana-6092	54	59	compute	compute	VERB
cana-6092	54	60	gradients	gradient	NOUN
cana-6092	54	61	through	through	ADP
cana-6092	54	62	physical	physical	ADJ
cana-6092	54	63	simulations	simulation	NOUN
cana-6092	54	64	,	,	PUNCT
cana-6092	54	65	enabling	enable	VERB
cana-6092	54	66	end	end	NOUN
cana-6092	54	67	-	-	PUNCT
cana-6092	54	68	to	to	ADP
cana-6092	54	69	-	-	PUNCT
cana-6092	54	70	end	end	NOUN
cana-6092	54	71	training	training	NOUN
cana-6092	54	72	of	of	ADP
cana-6092	54	73	networks	network	NOUN
cana-6092	54	74	that	that	PRON
cana-6092	54	75	respect	respect	VERB
cana-6092	54	76	physical	physical	ADJ
cana-6092	54	77	laws	law	NOUN
cana-6092	54	78	23	23	NUM
cana-6092	54	79	.	.	PUNCT
cana-6092	55	1	this	this	DET
cana-6092	55	2	approach	approach	NOUN
cana-6092	55	3	is	be	AUX
cana-6092	55	4	particularly	particularly	ADV
cana-6092	55	5	powerful	powerful	ADJ
cana-6092	55	6	for	for	ADP
cana-6092	55	7	problems	problem	NOUN
cana-6092	55	8	where	where	SCONJ
cana-6092	55	9	the	the	DET
cana-6092	55	10	forward	forward	ADJ
cana-6092	55	11	model	model	NOUN
cana-6092	55	12	is	be	AUX
cana-6092	55	13	differentiable	differentiable	ADJ
cana-6092	55	14	and	and	CCONJ
cana-6092	55	15	can	can	AUX
cana-6092	55	16	be	be	AUX
cana-6092	55	17	integrated	integrate	VERB
cana-6092	55	18	into	into	ADP
cana-6092	55	19	the	the	DET
cana-6092	55	20	computational	computational	ADJ
cana-6092	55	21	graph	graph	NOUN
cana-6092	55	22	.	.	PUNCT
cana-6092	56	1	model	model	NOUN
cana-6092	56	2	reduction	reduction	NOUN
cana-6092	56	3	techniques	technique	NOUN
cana-6092	56	4	reduce	reduce	VERB
cana-6092	56	5	computational	computational	ADJ
cana-6092	56	6	complexity	complexity	NOUN
cana-6092	56	7	by	by	ADP
cana-6092	56	8	learning	learn	VERB
cana-6092	56	9	low	low	ADJ
cana-6092	56	10	-	-	PUNCT
cana-6092	56	11	dimensional	dimensional	ADJ
cana-6092	56	12	representations	representation	NOUN
cana-6092	56	13	of	of	ADP
cana-6092	56	14	high	high	ADJ
cana-6092	56	15	-	-	PUNCT
cana-6092	56	16	dimensional	dimensional	ADJ
cana-6092	56	17	parameter	parameter	NOUN
cana-6092	56	18	spaces	space	VERB
cana-6092	56	19	47	47	NUM
cana-6092	56	20	.	.	PUNCT
cana-6092	57	1	techniques	technique	NOUN
cana-6092	57	2	such	such	ADJ
cana-6092	57	3	as	as	ADP
cana-6092	57	4	proper	proper	ADJ
cana-6092	57	5	orthogonal	orthogonal	ADJ
cana-6092	57	6	decomposition	decomposition	NOUN
cana-6092	57	7	(	(	PUNCT
cana-6092	57	8	pod	pod	NOUN
cana-6092	57	9	)	)	PUNCT
cana-6092	57	10	and	and	CCONJ
cana-6092	57	11	reduced	reduce	VERB
cana-6092	57	12	basis	basis	NOUN
cana-6092	57	13	methods	method	NOUN
cana-6092	57	14	can	can	AUX
cana-6092	57	15	be	be	AUX
cana-6092	57	16	integrated	integrate	VERB
cana-6092	57	17	with	with	ADP
cana-6092	57	18	neural	neural	ADJ
cana-6092	57	19	networks	network	NOUN
cana-6092	57	20	to	to	PART
cana-6092	57	21	handle	handle	VERB
cana-6092	57	22	large	large	ADJ
cana-6092	57	23	-	-	PUNCT
cana-6092	57	24	scale	scale	NOUN
cana-6092	57	25	problems	problem	NOUN
cana-6092	57	26	efficiently	efficiently	ADV
cana-6092	57	27	.	.	PUNCT
cana-6092	58	1	4.applications	4.application	NOUN
cana-6092	58	2	4.1	4.1	NUM
cana-6092	58	3	medical	medical	ADJ
cana-6092	58	4	imaging	imaging	NOUN
cana-6092	58	5	reconstruction	reconstruction	NOUN
cana-6092	58	6	medical	medical	ADJ
cana-6092	58	7	imaging	imaging	NOUN
cana-6092	58	8	modalities	modality	NOUN
cana-6092	58	9	including	include	VERB
cana-6092	58	10	computed	compute	VERB
cana-6092	58	11	tomography	tomography	NOUN
cana-6092	58	12	(	(	PUNCT
cana-6092	58	13	ct	ct	PROPN
cana-6092	58	14	)	)	PUNCT
cana-6092	58	15	,	,	PUNCT
cana-6092	58	16	magnetic	magnetic	ADJ
cana-6092	58	17	resonance	resonance	NOUN
cana-6092	58	18	imaging	imaging	NOUN
cana-6092	58	19	(	(	PUNCT
cana-6092	58	20	mri	mri	NOUN
cana-6092	58	21	)	)	PUNCT
cana-6092	58	22	,	,	PUNCT
cana-6092	58	23	and	and	CCONJ
cana-6092	58	24	positron	positron	NOUN
cana-6092	58	25	emission	emission	NOUN
cana-6092	58	26	tomography	tomography	NOUN
cana-6092	58	27	(	(	PUNCT
cana-6092	58	28	pet	pet	NOUN
cana-6092	58	29	)	)	PUNCT
cana-6092	58	30	inherently	inherently	ADV
cana-6092	58	31	involve	involve	VERB
cana-6092	58	32	inverse	inverse	NOUN
cana-6092	58	33	problems	problem	NOUN
cana-6092	58	34	where	where	SCONJ
cana-6092	58	35	the	the	DET
cana-6092	58	36	goal	goal	NOUN
cana-6092	58	37	is	be	AUX
cana-6092	58	38	to	to	PART
cana-6092	58	39	reconstruct	reconstruct	VERB
cana-6092	58	40	anatomical	anatomical	ADJ
cana-6092	58	41	or	or	CCONJ
cana-6092	58	42	functional	functional	ADJ
cana-6092	58	43	images	image	NOUN
cana-6092	58	44	from	from	ADP
cana-6092	58	45	measured	measured	ADJ
cana-6092	58	46	projections	projection	NOUN
cana-6092	58	47	or	or	CCONJ
cana-6092	58	48	signals	signal	NOUN
cana-6092	58	49	5	5	NUM
cana-6092	58	50	.	.	PUNCT
cana-6092	58	51	neural	neural	ADJ
cana-6092	58	52	network	network	NOUN
cana-6092	58	53	approaches	approach	NOUN
cana-6092	58	54	have	have	AUX
cana-6092	58	55	demonstrated	demonstrate	VERB
cana-6092	58	56	remarkable	remarkable	ADJ
cana-6092	58	57	success	success	NOUN
cana-6092	58	58	in	in	ADP
cana-6092	58	59	accelerating	accelerate	VERB
cana-6092	58	60	these	these	DET
cana-6092	58	61	reconstructions	reconstruction	NOUN
cana-6092	58	62	while	while	SCONJ
cana-6092	58	63	maintaining	maintain	VERB
cana-6092	58	64	or	or	CCONJ
cana-6092	58	65	improving	improve	VERB
cana-6092	58	66	image	image	NOUN
cana-6092	58	67	quality	quality	NOUN
cana-6092	58	68	.	.	PUNCT
cana-6092	59	1	for	for	ADP
cana-6092	59	2	mri	mri	NOUN
cana-6092	59	3	reconstruction	reconstruction	NOUN
cana-6092	59	4	from	from	ADP
cana-6092	59	5	undersampled	undersampled	ADJ
cana-6092	59	6	k	k	PROPN
cana-6092	59	7	-	-	PUNCT
cana-6092	59	8	space	space	NOUN
cana-6092	59	9	data	datum	NOUN
cana-6092	59	10	,	,	PUNCT
cana-6092	59	11	neural	neural	ADJ
cana-6092	59	12	networks	network	NOUN
cana-6092	59	13	can	can	AUX
cana-6092	59	14	learn	learn	VERB
cana-6092	59	15	mappings	mapping	NOUN
cana-6092	59	16	from	from	ADP
cana-6092	59	17	undersampled	undersampled	ADJ
cana-6092	59	18	reconstructions	reconstruction	NOUN
cana-6092	59	19	to	to	ADP
cana-6092	59	20	high	high	ADJ
cana-6092	59	21	-	-	PUNCT
cana-6092	59	22	quality	quality	NOUN
cana-6092	59	23	images	image	NOUN
cana-6092	59	24	,	,	PUNCT
cana-6092	59	25	effectively	effectively	ADV
cana-6092	59	26	filling	fill	VERB
cana-6092	59	27	in	in	ADP
cana-6092	59	28	missing	miss	VERB
cana-6092	59	29	information	information	NOUN
cana-6092	59	30	based	base	VERB
cana-6092	59	31	on	on	ADP
cana-6092	59	32	training	training	NOUN
cana-6092	59	33	data	datum	NOUN
cana-6092	59	34	patterns	pattern	NOUN
cana-6092	59	35	5	5	NUM
cana-6092	59	36	.	.	PUNCT
cana-6092	59	37	similarly	similarly	ADV
cana-6092	59	38	,	,	PUNCT
cana-6092	59	39	in	in	ADP
cana-6092	59	40	ct	ct	PROPN
cana-6092	59	41	reconstruction	reconstruction	NOUN
cana-6092	59	42	,	,	PUNCT
cana-6092	59	43	neural	neural	ADJ
cana-6092	59	44	networks	network	NOUN
cana-6092	59	45	have	have	AUX
cana-6092	59	46	been	be	AUX
cana-6092	59	47	used	use	VERB
cana-6092	59	48	to	to	PART
cana-6092	59	49	reduce	reduce	VERB
cana-6092	59	50	radiation	radiation	NOUN
cana-6092	59	51	dose	dose	VERB
cana-6092	59	52	by	by	ADP
cana-6092	59	53	producing	produce	VERB
cana-6092	59	54	high	high	ADJ
cana-6092	59	55	-	-	PUNCT
cana-6092	59	56	quality	quality	NOUN
cana-6092	59	57	images	image	NOUN
cana-6092	59	58	from	from	ADP
cana-6092	59	59	limited	limited	ADJ
cana-6092	59	60	-	-	PUNCT
cana-6092	59	61	angle	angle	NOUN
cana-6092	59	62	or	or	CCONJ
cana-6092	59	63	sparse	sparse	ADJ
cana-6092	59	64	-	-	PUNCT
cana-6092	59	65	view	view	NOUN
cana-6092	59	66	projections	projection	NOUN
cana-6092	59	67	5	5	NUM
cana-6092	59	68	.	.	PUNCT
cana-6092	60	1	these	these	DET
cana-6092	60	2	approaches	approach	NOUN
cana-6092	60	3	typically	typically	ADV
cana-6092	60	4	demonstrate	demonstrate	VERB
cana-6092	60	5	significant	significant	ADJ
cana-6092	60	6	acceleration	acceleration	NOUN
cana-6092	60	7	compared	compare	VERB
cana-6092	60	8	to	to	ADP
cana-6092	60	9	iterative	iterative	ADJ
cana-6092	60	10	reconstruction	reconstruction	NOUN
cana-6092	60	11	methods	method	NOUN
cana-6092	60	12	,	,	PUNCT
cana-6092	60	13	once	once	SCONJ
cana-6092	60	14	the	the	DET
cana-6092	60	15	models	model	NOUN
cana-6092	60	16	are	be	AUX
cana-6092	60	17	trained	train	VERB
cana-6092	60	18	.	.	PUNCT
cana-6092	61	1	for	for	ADP
cana-6092	61	2	example	example	NOUN
cana-6092	61	3	,	,	PUNCT
cana-6092	61	4	neural	neural	ADJ
cana-6092	61	5	network	network	NOUN
cana-6092	61	6	-	-	PUNCT
cana-6092	61	7	based	base	VERB
cana-6092	61	8	mri	mri	NOUN
cana-6092	61	9	reconstruction	reconstruction	NOUN
cana-6092	61	10	can	can	AUX
cana-6092	61	11	achieve	achieve	VERB
cana-6092	61	12	near	near	ADV
cana-6092	61	13	-	-	PUNCT
cana-6092	61	14	instantaneous	instantaneous	ADJ
cana-6092	61	15	reconstruction	reconstruction	NOUN
cana-6092	61	16	compared	compare	VERB
cana-6092	61	17	to	to	ADP
cana-6092	61	18	minutes	minute	NOUN
cana-6092	61	19	or	or	CCONJ
cana-6092	61	20	hours	hour	NOUN
cana-6092	61	21	for	for	ADP
cana-6092	61	22	conventional	conventional	ADJ
cana-6092	61	23	compressed	compress	VERB
cana-6092	61	24	sensing	sense	VERB
cana-6092	61	25	approaches	approach	NOUN
cana-6092	61	26	,	,	PUNCT
cana-6092	61	27	facilitating	facilitate	VERB
cana-6092	61	28	real	real	ADJ
cana-6092	61	29	-	-	PUNCT
cana-6092	61	30	time	time	NOUN
cana-6092	61	31	imaging	imaging	NOUN
cana-6092	61	32	applications	application	NOUN
cana-6092	61	33	5	5	NUM
cana-6092	61	34	.	.	X
cana-6092	61	35	4.2	4.2	NUM
cana-6092	61	36	geophysical	geophysical	ADJ
cana-6092	61	37	inversion	inversion	NOUN
cana-6092	61	38	geophysical	geophysical	ADJ
cana-6092	61	39	inverse	inverse	NOUN
cana-6092	61	40	problems	problem	NOUN
cana-6092	61	41	involve	involve	VERB
cana-6092	61	42	estimating	estimate	VERB
cana-6092	61	43	subsurface	subsurface	NOUN
cana-6092	61	44	properties	property	NOUN
cana-6092	61	45	from	from	ADP
cana-6092	61	46	surface	surface	NOUN
cana-6092	61	47	measurements	measurement	NOUN
cana-6092	61	48	,	,	PUNCT
cana-6092	61	49	such	such	ADJ
cana-6092	61	50	as	as	ADP
cana-6092	61	51	seismic	seismic	ADJ
cana-6092	61	52	data	datum	NOUN
cana-6092	61	53	,	,	PUNCT
cana-6092	61	54	electromagnetic	electromagnetic	ADJ
cana-6092	61	55	data	datum	NOUN
cana-6092	61	56	,	,	PUNCT
cana-6092	61	57	or	or	CCONJ
cana-6092	61	58	gravity	gravity	NOUN
cana-6092	61	59	data	datum	NOUN
cana-6092	61	60	6	6	NUM
cana-6092	61	61	.	.	PUNCT
cana-6092	62	1	these	these	DET
cana-6092	62	2	problems	problem	NOUN
cana-6092	62	3	are	be	AUX
cana-6092	62	4	particularly	particularly	ADV
cana-6092	62	5	challenging	challenging	ADJ
cana-6092	62	6	due	due	ADJ
cana-6092	62	7	to	to	ADP
cana-6092	62	8	the	the	DET
cana-6092	62	9	highdimensional	highdimensional	ADJ
cana-6092	62	10	parameter	parameter	NOUN
cana-6092	62	11	spaces	space	NOUN
cana-6092	62	12	,	,	PUNCT
cana-6092	62	13	complex	complex	ADJ
cana-6092	62	14	physical	physical	ADJ
cana-6092	62	15	relationships	relationship	NOUN
cana-6092	62	16	,	,	PUNCT
cana-6092	62	17	and	and	CCONJ
cana-6092	62	18	limited	limited	ADJ
cana-6092	62	19	measurement	measurement	NOUN
cana-6092	62	20	data	datum	NOUN
cana-6092	62	21	.	.	PUNCT
cana-6092	63	1	neural	neural	ADJ
cana-6092	63	2	networks	network	NOUN
cana-6092	63	3	have	have	AUX
cana-6092	63	4	been	be	AUX
cana-6092	63	5	applied	apply	VERB
cana-6092	63	6	to	to	ADP
cana-6092	63	7	various	various	ADJ
cana-6092	63	8	geophysical	geophysical	ADJ
cana-6092	63	9	inversion	inversion	NOUN
cana-6092	63	10	problems	problem	NOUN
cana-6092	63	11	,	,	PUNCT
cana-6092	63	12	including	include	VERB
cana-6092	63	13	seismic	seismic	ADJ
cana-6092	63	14	impedance	impedance	NOUN
cana-6092	63	15	inversion	inversion	NOUN
cana-6092	63	16	,	,	PUNCT
cana-6092	63	17	electromagnetic	electromagnetic	ADJ
cana-6092	63	18	inversion	inversion	NOUN
cana-6092	63	19	,	,	PUNCT
cana-6092	63	20	and	and	CCONJ
cana-6092	63	21	gravity	gravity	NOUN
cana-6092	63	22	inversion	inversion	NOUN
cana-6092	63	23	6	6	NUM
cana-6092	63	24	.	.	PUNCT
cana-6092	64	1	for	for	ADP
cana-6092	64	2	example	example	NOUN
cana-6092	64	3	,	,	PUNCT
cana-6092	64	4	in	in	ADP
cana-6092	64	5	seismic	seismic	ADJ
cana-6092	64	6	inversion	inversion	NOUN
cana-6092	64	7	,	,	PUNCT
cana-6092	64	8	neural	neural	ADJ
cana-6092	64	9	networks	network	NOUN
cana-6092	64	10	can	can	AUX
cana-6092	64	11	learn	learn	VERB
cana-6092	64	12	to	to	PART
cana-6092	64	13	map	map	VERB
cana-6092	64	14	seismic	seismic	ADJ
cana-6092	64	15	waveforms	waveform	NOUN
cana-6092	64	16	to	to	ADP
cana-6092	64	17	subsurface	subsurface	NOUN
cana-6092	64	18	properties	property	NOUN
cana-6092	64	19	such	such	ADJ
cana-6092	64	20	as	as	ADP
cana-6092	64	21	velocity	velocity	NOUN
cana-6092	64	22	,	,	PUNCT
cana-6092	64	23	density	density	NOUN
cana-6092	64	24	,	,	PUNCT
cana-6092	64	25	and	and	CCONJ
cana-6092	64	26	impedance	impedance	NOUN
cana-6092	64	27	36	36	NUM
cana-6092	64	28	.	.	PUNCT
cana-6092	65	1	the	the	DET
cana-6092	65	2	proposed	propose	VERB
cana-6092	65	3	framework	framework	NOUN
cana-6092	65	4	has	have	AUX
cana-6092	65	5	demonstrated	demonstrate	VERB
cana-6092	65	6	particular	particular	ADJ
cana-6092	65	7	effectiveness	effectiveness	NOUN
cana-6092	65	8	for	for	ADP
cana-6092	65	9	problems	problem	NOUN
cana-6092	65	10	with	with	ADP
cana-6092	65	11	limited	limited	ADJ
cana-6092	65	12	data	datum	NOUN
cana-6092	65	13	or	or	CCONJ
cana-6092	65	14	complex	complex	ADJ
cana-6092	65	15	geological	geological	ADJ
cana-6092	65	16	settings	setting	NOUN
cana-6092	65	17	where	where	SCONJ
cana-6092	65	18	traditional	traditional	ADJ
cana-6092	65	19	methods	method	NOUN
cana-6092	65	20	struggle	struggle	VERB
cana-6092	65	21	.	.	PUNCT
cana-6092	66	1	by	by	ADP
cana-6092	66	2	learning	learn	VERB
cana-6092	66	3	prior	prior	ADJ
cana-6092	66	4	information	information	NOUN
cana-6092	66	5	from	from	ADP
cana-6092	66	6	existing	exist	VERB
cana-6092	66	7	geological	geological	ADJ
cana-6092	66	8	models	model	NOUN
cana-6092	66	9	or	or	CCONJ
cana-6092	66	10	well	well	ADV
cana-6092	66	11	logs	log	NOUN
cana-6092	66	12	,	,	PUNCT
cana-6092	66	13	neural	neural	ADJ
cana-6092	66	14	networks	network	NOUN
cana-6092	66	15	can	can	AUX
cana-6092	66	16	produce	produce	VERB
cana-6092	66	17	more	more	ADV
cana-6092	66	18	accurate	accurate	ADJ
cana-6092	66	19	and	and	CCONJ
cana-6092	66	20	geologically	geologically	ADV
cana-6092	66	21	plausible	plausible	ADJ
cana-6092	66	22	inversion	inversion	NOUN
cana-6092	66	23	results	result	VERB
cana-6092	66	24	36	36	NUM
cana-6092	66	25	.	.	PUNCT
cana-6092	67	1	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	ADJ
cana-6092	67	2	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	67	3	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	67	4	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	67	5	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	ADJ
cana-6092	67	6	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	67	7	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	67	8	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	67	9	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	67	10	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	67	11	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	67	12	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	NOUN
cana-6092	67	13	https://www.smartchair.org/hp/cipa2025/home/	https://www.smartchair.org/hp/cipa2025/home/	NOUN
cana-6092	67	14	https://www.smartchair.org/hp/cipa2025/home/	https://www.smartchair.org/hp/cipa2025/home/	PROPN
cana-6092	67	15	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	67	16	https://www.smartchair.org/hp/cipa2025/home/	https://www.smartchair.org/hp/cipa2025/home/	PROPN
cana-6092	67	17	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	67	18	https://www.smartchair.org/hp/cipa2025/home/	https://www.smartchair.org/hp/cipa2025/home/	PROPN
cana-6092	67	19	communications	communication	NOUN
cana-6092	67	20	on	on	ADP
cana-6092	67	21	applied	apply	VERB
cana-6092	67	22	nonlinear	nonlinear	ADJ
cana-6092	67	23	analysis	analysis	NOUN
cana-6092	67	24	issn	issn	NOUN
cana-6092	67	25	:	:	PUNCT
cana-6092	67	26	1074	1074	NUM
cana-6092	67	27	-	-	PUNCT
cana-6092	67	28	133x	133x	NUM
cana-6092	67	29	vol	vol	NOUN
cana-6092	67	30	31	31	NUM
cana-6092	67	31	no	no	NOUN
cana-6092	67	32	.	.	NOUN
cana-6092	67	33	2	2	NUM
cana-6092	67	34	(	(	PUNCT
cana-6092	67	35	2024	2024	NUM
cana-6092	67	36	)	)	PUNCT
cana-6092	67	37	504	504	NUM
cana-6092	67	38	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	67	39	4.3	4.3	NUM
cana-6092	67	40	pde	pde	NOUN
cana-6092	67	41	-	-	PUNCT
cana-6092	67	42	based	base	VERB
cana-6092	67	43	inverse	inverse	NOUN
cana-6092	67	44	problems	problem	NOUN
cana-6092	68	1	inverse	inverse	VERB
cana-6092	68	2	problems	problem	NOUN
cana-6092	68	3	involving	involve	VERB
cana-6092	68	4	partial	partial	ADJ
cana-6092	68	5	differential	differential	ADJ
cana-6092	68	6	equations	equation	NOUN
cana-6092	68	7	(	(	PUNCT
cana-6092	68	8	pdes	pde	NOUN
cana-6092	68	9	)	)	PUNCT
cana-6092	68	10	arise	arise	NOUN
cana-6092	68	11	in	in	ADP
cana-6092	68	12	numerous	numerous	ADJ
cana-6092	68	13	domains	domain	NOUN
cana-6092	68	14	,	,	PUNCT
cana-6092	68	15	including	include	VERB
cana-6092	68	16	heat	heat	NOUN
cana-6092	68	17	conduction	conduction	NOUN
cana-6092	68	18	,	,	PUNCT
cana-6092	68	19	elasticity	elasticity	NOUN
cana-6092	68	20	,	,	PUNCT
cana-6092	68	21	electromagnetics	electromagnetic	NOUN
cana-6092	68	22	,	,	PUNCT
cana-6092	68	23	and	and	CCONJ
cana-6092	68	24	fluid	fluid	ADJ
cana-6092	68	25	dynamics	dynamic	NOUN
cana-6092	68	26	47	47	NUM
cana-6092	68	27	.	.	PUNCT
cana-6092	69	1	these	these	DET
cana-6092	69	2	problems	problem	NOUN
cana-6092	69	3	involve	involve	VERB
cana-6092	69	4	estimating	estimate	VERB
cana-6092	69	5	parameters	parameter	NOUN
cana-6092	69	6	,	,	PUNCT
cana-6092	69	7	initial	initial	ADJ
cana-6092	69	8	conditions	condition	NOUN
cana-6092	69	9	,	,	PUNCT
cana-6092	69	10	or	or	CCONJ
cana-6092	69	11	boundary	boundary	ADJ
cana-6092	69	12	conditions	condition	NOUN
cana-6092	69	13	from	from	ADP
cana-6092	69	14	solution	solution	NOUN
cana-6092	69	15	data	datum	NOUN
cana-6092	69	16	.	.	PUNCT
cana-6092	70	1	physics	physics	NOUN
cana-6092	70	2	-	-	PUNCT
cana-6092	70	3	informed	inform	VERB
cana-6092	70	4	neural	neural	ADJ
cana-6092	70	5	networks	network	NOUN
cana-6092	70	6	(	(	PUNCT
cana-6092	70	7	pinns	pinns	ADV
cana-6092	70	8	)	)	PUNCT
cana-6092	70	9	have	have	AUX
cana-6092	70	10	shown	show	VERB
cana-6092	70	11	remarkable	remarkable	ADJ
cana-6092	70	12	success	success	NOUN
cana-6092	70	13	for	for	ADP
cana-6092	70	14	pde	pde	NOUN
cana-6092	70	15	-	-	PUNCT
cana-6092	70	16	based	base	VERB
cana-6092	70	17	inverse	inverse	NOUN
cana-6092	70	18	problems	problem	NOUN
cana-6092	70	19	47	47	NUM
cana-6092	70	20	.	.	PUNCT
cana-6092	71	1	for	for	ADP
cana-6092	71	2	example	example	NOUN
cana-6092	71	3	,	,	PUNCT
cana-6092	71	4	for	for	ADP
cana-6092	71	5	the	the	DET
cana-6092	71	6	2d	2d	NUM
cana-6092	71	7	heat	heat	NOUN
cana-6092	71	8	equation	equation	NOUN
cana-6092	71	9	with	with	ADP
cana-6092	71	10	unknown	unknown	ADJ
cana-6092	71	11	thermal	thermal	ADJ
cana-6092	71	12	conductivity	conductivity	NOUN
cana-6092	71	13	,	,	PUNCT
cana-6092	71	14	pinns	pinn	NOUN
cana-6092	71	15	can	can	AUX
cana-6092	71	16	simultaneously	simultaneously	ADV
cana-6092	71	17	estimate	estimate	VERB
cana-6092	71	18	the	the	DET
cana-6092	71	19	conductivity	conductivity	NOUN
cana-6092	71	20	field	field	NOUN
cana-6092	71	21	and	and	CCONJ
cana-6092	71	22	temperature	temperature	NOUN
cana-6092	71	23	distribution	distribution	NOUN
cana-6092	71	24	from	from	ADP
cana-6092	71	25	limited	limited	ADJ
cana-6092	71	26	measurement	measurement	NOUN
cana-6092	71	27	data	datum	NOUN
cana-6092	71	28	4	4	NUM
cana-6092	71	29	.	.	PUNCT
cana-6092	71	30	similarly	similarly	ADV
cana-6092	71	31	,	,	PUNCT
cana-6092	71	32	for	for	ADP
cana-6092	71	33	the	the	DET
cana-6092	71	34	wave	wave	NOUN
cana-6092	71	35	equation	equation	NOUN
cana-6092	71	36	,	,	PUNCT
cana-6092	71	37	pinns	pinn	NOUN
cana-6092	71	38	can	can	AUX
cana-6092	71	39	estimate	estimate	VERB
cana-6092	71	40	wave	wave	NOUN
cana-6092	71	41	speeds	speed	NOUN
cana-6092	71	42	from	from	ADP
cana-6092	71	43	waveform	waveform	NOUN
cana-6092	71	44	data	datum	NOUN
cana-6092	71	45	4	4	NUM
cana-6092	71	46	.	.	PUNCT
cana-6092	72	1	the	the	DET
cana-6092	72	2	framework	framework	NOUN
cana-6092	72	3	also	also	ADV
cana-6092	72	4	handles	handle	VERB
cana-6092	72	5	problems	problem	NOUN
cana-6092	72	6	with	with	ADP
cana-6092	72	7	irregular	irregular	ADJ
cana-6092	72	8	geometries	geometry	NOUN
cana-6092	72	9	and	and	CCONJ
cana-6092	72	10	complex	complex	ADJ
cana-6092	72	11	boundary	boundary	ADJ
cana-6092	72	12	conditions	condition	NOUN
cana-6092	72	13	that	that	PRON
cana-6092	72	14	challenge	challenge	VERB
cana-6092	72	15	traditional	traditional	ADJ
cana-6092	72	16	numerical	numerical	ADJ
cana-6092	72	17	methods	method	NOUN
cana-6092	72	18	47	47	NUM
cana-6092	72	19	.	.	PUNCT
cana-6092	73	1	by	by	ADP
cana-6092	73	2	using	use	VERB
cana-6092	73	3	coordinatebased	coordinatebase	VERB
cana-6092	73	4	networks	network	NOUN
cana-6092	73	5	that	that	PRON
cana-6092	73	6	take	take	VERB
cana-6092	73	7	spatial	spatial	ADJ
cana-6092	73	8	and	and	CCONJ
cana-6092	73	9	temporal	temporal	ADJ
cana-6092	73	10	coordinates	coordinate	NOUN
cana-6092	73	11	as	as	ADP
cana-6092	73	12	inputs	input	NOUN
cana-6092	73	13	,	,	PUNCT
cana-6092	73	14	pinns	pinn	NOUN
cana-6092	73	15	can	can	AUX
cana-6092	73	16	represent	represent	VERB
cana-6092	73	17	solutions	solution	NOUN
cana-6092	73	18	continuously	continuously	ADV
cana-6092	73	19	throughout	throughout	ADP
cana-6092	73	20	the	the	DET
cana-6092	73	21	domain	domain	NOUN
cana-6092	73	22	without	without	ADP
cana-6092	73	23	requiring	require	VERB
cana-6092	73	24	mesh	mesh	NOUN
cana-6092	73	25	generation	generation	NOUN
cana-6092	73	26	4	4	NUM
cana-6092	73	27	.	.	X
cana-6092	73	28	4.4	4.4	NUM
cana-6092	73	29	cross	cross	ADJ
cana-6092	73	30	-	-	ADJ
cana-6092	73	31	domain	domain	ADJ
cana-6092	73	32	applications	application	NOUN
cana-6092	73	33	the	the	DET
cana-6092	73	34	neural	neural	ADJ
cana-6092	73	35	network	network	NOUN
cana-6092	73	36	framework	framework	NOUN
cana-6092	73	37	demonstrates	demonstrate	VERB
cana-6092	73	38	versatility	versatility	NOUN
cana-6092	73	39	across	across	ADP
cana-6092	73	40	diverse	diverse	ADJ
cana-6092	73	41	application	application	NOUN
cana-6092	73	42	domains	domain	NOUN
cana-6092	73	43	:	:	PUNCT
cana-6092	73	44	astronomical	astronomical	ADJ
cana-6092	73	45	imaging	imaging	NOUN
cana-6092	73	46	involves	involve	VERB
cana-6092	73	47	reconstructing	reconstruct	VERB
cana-6092	73	48	images	image	NOUN
cana-6092	73	49	from	from	ADP
cana-6092	73	50	noisy	noisy	ADJ
cana-6092	73	51	,	,	PUNCT
cana-6092	73	52	incomplete	incomplete	ADJ
cana-6092	73	53	,	,	PUNCT
cana-6092	73	54	or	or	CCONJ
cana-6092	73	55	interferometric	interferometric	ADJ
cana-6092	73	56	measurements	measurement	NOUN
cana-6092	73	57	5	5	NUM
cana-6092	73	58	.	.	PUNCT
cana-6092	73	59	neural	neural	ADJ
cana-6092	73	60	networks	network	NOUN
cana-6092	73	61	can	can	AUX
cana-6092	73	62	learn	learn	VERB
cana-6092	73	63	effective	effective	ADJ
cana-6092	73	64	priors	prior	NOUN
cana-6092	73	65	from	from	ADP
cana-6092	73	66	existing	exist	VERB
cana-6092	73	67	astronomical	astronomical	ADJ
cana-6092	73	68	images	image	NOUN
cana-6092	73	69	,	,	PUNCT
cana-6092	73	70	enabling	enable	VERB
cana-6092	73	71	superior	superior	ADJ
cana-6092	73	72	reconstruction	reconstruction	NOUN
cana-6092	73	73	compared	compare	VERB
cana-6092	73	74	to	to	ADP
cana-6092	73	75	traditional	traditional	ADJ
cana-6092	73	76	hand	hand	NOUN
cana-6092	73	77	-	-	PUNCT
cana-6092	73	78	crafted	craft	VERB
cana-6092	73	79	regularizers	regularizer	NOUN
cana-6092	73	80	5	5	NUM
cana-6092	73	81	.	.	PUNCT
cana-6092	73	82	material	material	NOUN
cana-6092	73	83	science	science	NOUN
cana-6092	73	84	inverse	inverse	NOUN
cana-6092	73	85	problems	problem	NOUN
cana-6092	73	86	include	include	VERB
cana-6092	73	87	estimating	estimate	VERB
cana-6092	73	88	material	material	NOUN
cana-6092	73	89	properties	property	NOUN
cana-6092	73	90	from	from	ADP
cana-6092	73	91	measurements	measurement	NOUN
cana-6092	73	92	or	or	CCONJ
cana-6092	73	93	designing	designing	NOUN
cana-6092	73	94	microstructures	microstructure	NOUN
cana-6092	73	95	with	with	ADP
cana-6092	73	96	desired	desire	VERB
cana-6092	73	97	properties	property	NOUN
cana-6092	73	98	3	3	NUM
cana-6092	73	99	.	.	PUNCT
cana-6092	73	100	neural	neural	ADJ
cana-6092	73	101	networks	network	NOUN
cana-6092	73	102	,	,	PUNCT
cana-6092	73	103	particularly	particularly	ADV
cana-6092	73	104	gans	gan	NOUN
cana-6092	73	105	,	,	PUNCT
cana-6092	73	106	have	have	AUX
cana-6092	73	107	been	be	AUX
cana-6092	73	108	used	use	VERB
cana-6092	73	109	to	to	PART
cana-6092	73	110	generate	generate	VERB
cana-6092	73	111	microstructures	microstructure	NOUN
cana-6092	73	112	conditioned	condition	VERB
cana-6092	73	113	on	on	ADP
cana-6092	73	114	continuous	continuous	ADJ
cana-6092	73	115	property	property	NOUN
cana-6092	73	116	values	value	NOUN
cana-6092	73	117	,	,	PUNCT
cana-6092	73	118	enabling	enable	VERB
cana-6092	73	119	inverse	inverse	NOUN
cana-6092	73	120	design	design	NOUN
cana-6092	73	121	of	of	ADP
cana-6092	73	122	materials	material	NOUN
cana-6092	73	123	3	3	NUM
cana-6092	73	124	.	.	PUNCT
cana-6092	74	1	environmental	environmental	ADJ
cana-6092	74	2	monitoring	monitoring	NOUN
cana-6092	74	3	involves	involve	VERB
cana-6092	74	4	estimating	estimate	VERB
cana-6092	74	5	pollution	pollution	NOUN
cana-6092	74	6	sources	source	NOUN
cana-6092	74	7	,	,	PUNCT
cana-6092	74	8	geological	geological	ADJ
cana-6092	74	9	parameters	parameter	NOUN
cana-6092	74	10	,	,	PUNCT
cana-6092	74	11	or	or	CCONJ
cana-6092	74	12	atmospheric	atmospheric	ADJ
cana-6092	74	13	conditions	condition	NOUN
cana-6092	74	14	from	from	ADP
cana-6092	74	15	limited	limited	ADJ
cana-6092	74	16	sensor	sensor	NOUN
cana-6092	74	17	data	datum	NOUN
cana-6092	74	18	56	56	NUM
cana-6092	74	19	.	.	PUNCT
cana-6092	75	1	neural	neural	ADJ
cana-6092	75	2	networks	network	NOUN
cana-6092	75	3	can	can	AUX
cana-6092	75	4	integrate	integrate	VERB
cana-6092	75	5	physical	physical	ADJ
cana-6092	75	6	models	model	NOUN
cana-6092	75	7	with	with	ADP
cana-6092	75	8	measurement	measurement	NOUN
cana-6092	75	9	data	datum	NOUN
cana-6092	75	10	to	to	PART
cana-6092	75	11	provide	provide	VERB
cana-6092	75	12	accurate	accurate	ADJ
cana-6092	75	13	estimates	estimate	NOUN
cana-6092	75	14	with	with	ADP
cana-6092	75	15	uncertainty	uncertainty	NOUN
cana-6092	75	16	quantification	quantification	NOUN
cana-6092	75	17	5	5	NUM
cana-6092	75	18	.	.	PUNCT
cana-6092	75	19	application	application	NOUN
cana-6092	75	20	domain	domain	NOUN
cana-6092	75	21	traditional	traditional	ADJ
cana-6092	75	22	method	method	NOUN
cana-6092	75	23	neural	neural	ADJ
cana-6092	75	24	network	network	NOUN
cana-6092	75	25	approach	approach	NOUN
cana-6092	75	26	performance	performance	NOUN
cana-6092	75	27	improvement	improvement	NOUN
cana-6092	75	28	mri	mri	NOUN
cana-6092	75	29	reconstruction	reconstruction	NOUN
cana-6092	75	30	compressed	compress	VERB
cana-6092	75	31	sensing	sense	VERB
cana-6092	75	32	u	u	NOUN
cana-6092	75	33	-	-	NOUN
cana-6092	75	34	net	net	ADJ
cana-6092	75	35	with	with	ADP
cana-6092	75	36	adversarial	adversarial	ADJ
cana-6092	75	37	loss	loss	NOUN
cana-6092	75	38	2	2	NUM
cana-6092	75	39	-	-	PUNCT
cana-6092	75	40	4×	4×	NOUN
cana-6092	75	41	faster	fast	ADJ
cana-6092	75	42	acquisition	acquisition	NOUN
cana-6092	75	43	,	,	PUNCT
cana-6092	75	44	similar	similar	ADJ
cana-6092	75	45	quality	quality	NOUN
cana-6092	75	46	5	5	NUM
cana-6092	75	47	seismic	seismic	ADJ
cana-6092	75	48	inversion	inversion	NOUN
cana-6092	75	49	full	full	ADJ
cana-6092	75	50	waveform	waveform	NOUN
cana-6092	75	51	inversion	inversion	NOUN
cana-6092	75	52	conditional	conditional	ADJ
cana-6092	75	53	gan	gan	PROPN
cana-6092	75	54	improved	improve	VERB
cana-6092	75	55	geological	geological	ADJ
cana-6092	75	56	realism	realism	NOUN
cana-6092	75	57	,	,	PUNCT
cana-6092	75	58	10×	10×	NUM
cana-6092	75	59	acceleration	acceleration	NOUN
cana-6092	75	60	3	3	NUM
cana-6092	75	61	heat	heat	NOUN
cana-6092	75	62	equation	equation	NOUN
cana-6092	75	63	inverse	inverse	NOUN
cana-6092	75	64	gradient	gradient	NOUN
cana-6092	75	65	-	-	PUNCT
cana-6092	75	66	based	base	VERB
cana-6092	75	67	optimization	optimization	NOUN
cana-6092	75	68	physics	physics	NOUN
cana-6092	75	69	-	-	PUNCT
cana-6092	75	70	informed	inform	VERB
cana-6092	75	71	neural	neural	ADJ
cana-6092	75	72	network	network	NOUN
cana-6092	75	73	handles	handle	VERB
cana-6092	75	74	irregular	irregular	ADJ
cana-6092	75	75	geometries	geometry	NOUN
cana-6092	75	76	,	,	PUNCT
cana-6092	75	77	no	no	DET
cana-6092	75	78	mesh	mesh	NOUN
cana-6092	75	79	required	require	VERB
cana-6092	75	80	4	4	NUM
cana-6092	75	81	material	material	NOUN
cana-6092	75	82	design	design	NOUN
cana-6092	75	83	iterative	iterative	NOUN
cana-6092	75	84	optimization	optimization	NOUN
cana-6092	75	85	gan	gin	VERB
cana-6092	75	86	with	with	ADP
cana-6092	75	87	binary	binary	NOUN
cana-6092	75	88	embedding	embed	VERB
cana-6092	75	89	precise	precise	ADJ
cana-6092	75	90	property	property	NOUN
cana-6092	75	91	control	control	NOUN
cana-6092	75	92	,	,	PUNCT
cana-6092	75	93	diverse	diverse	ADJ
cana-6092	75	94	solutions	solution	NOUN
cana-6092	75	95	3	3	NUM
cana-6092	75	96	table	table	NOUN
cana-6092	75	97	3	3	NUM
cana-6092	75	98	:	:	PUNCT
cana-6092	75	99	performance	performance	NOUN
cana-6092	75	100	comparison	comparison	NOUN
cana-6092	75	101	across	across	ADP
cana-6092	75	102	application	application	NOUN
cana-6092	75	103	domains	domain	NOUN
cana-6092	75	104	5.challenges	5.challenges	NUM
cana-6092	75	105	and	and	CCONJ
cana-6092	75	106	limitations	limitation	NOUN
cana-6092	75	107	5.1	5.1	NUM
cana-6092	75	108	theoretical	theoretical	ADJ
cana-6092	75	109	guarantees	guarantee	NOUN
cana-6092	75	110	and	and	CCONJ
cana-6092	75	111	interpretability	interpretability	NOUN
cana-6092	75	112	while	while	SCONJ
cana-6092	75	113	empirical	empirical	ADJ
cana-6092	75	114	results	result	NOUN
cana-6092	75	115	have	have	AUX
cana-6092	75	116	demonstrated	demonstrate	VERB
cana-6092	75	117	the	the	DET
cana-6092	75	118	effectiveness	effectiveness	NOUN
cana-6092	75	119	of	of	ADP
cana-6092	75	120	neural	neural	ADJ
cana-6092	75	121	networks	network	NOUN
cana-6092	75	122	for	for	ADP
cana-6092	75	123	inverse	inverse	NOUN
cana-6092	75	124	problems	problem	NOUN
cana-6092	75	125	,	,	PUNCT
cana-6092	75	126	theoretical	theoretical	ADJ
cana-6092	75	127	guarantees	guarantee	NOUN
cana-6092	75	128	regarding	regard	VERB
cana-6092	75	129	convergence	convergence	NOUN
cana-6092	75	130	,	,	PUNCT
cana-6092	75	131	stability	stability	NOUN
cana-6092	75	132	,	,	PUNCT
cana-6092	75	133	and	and	CCONJ
cana-6092	75	134	solution	solution	NOUN
cana-6092	75	135	quality	quality	NOUN
cana-6092	75	136	remain	remain	VERB
cana-6092	75	137	limited	limited	ADJ
cana-6092	75	138	compared	compare	VERB
cana-6092	75	139	to	to	ADP
cana-6092	75	140	traditional	traditional	ADJ
cana-6092	75	141	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	142	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	75	143	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	144	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	ADP
cana-6092	75	145	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	146	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	147	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	148	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	75	149	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	150	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	75	151	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	75	152	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	75	153	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	75	154	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	75	155	https://www.smartchair.org/hp/cipa2025/home/	https://www.smartchair.org/hp/cipa2025/home/	PROPN
cana-6092	75	156	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	75	157	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	75	158	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	75	159	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	75	160	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	75	161	communications	communication	NOUN
cana-6092	75	162	on	on	ADP
cana-6092	75	163	applied	apply	VERB
cana-6092	75	164	nonlinear	nonlinear	ADJ
cana-6092	75	165	analysis	analysis	NOUN
cana-6092	75	166	issn	issn	NOUN
cana-6092	75	167	:	:	PUNCT
cana-6092	75	168	1074	1074	NUM
cana-6092	75	169	-	-	PUNCT
cana-6092	75	170	133x	133x	NUM
cana-6092	75	171	vol	vol	NOUN
cana-6092	75	172	31	31	NUM
cana-6092	75	173	no	no	NOUN
cana-6092	75	174	.	.	NOUN
cana-6092	75	175	2	2	NUM
cana-6092	75	176	(	(	PUNCT
cana-6092	75	177	2024	2024	NUM
cana-6092	75	178	)	)	PUNCT
cana-6092	75	179	505	505	NUM
cana-6092	75	180	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	75	181	regularization	regularization	NOUN
cana-6092	75	182	methods	method	NOUN
cana-6092	75	183	1	1	NUM
cana-6092	75	184	.	.	PUNCT
cana-6092	76	1	the	the	DET
cana-6092	76	2	black	black	ADJ
cana-6092	76	3	-	-	PUNCT
cana-6092	76	4	box	box	NOUN
cana-6092	76	5	nature	nature	NOUN
cana-6092	76	6	of	of	ADP
cana-6092	76	7	deep	deep	ADJ
cana-6092	76	8	neural	neural	ADJ
cana-6092	76	9	networks	network	NOUN
cana-6092	76	10	also	also	ADV
cana-6092	76	11	raises	raise	VERB
cana-6092	76	12	concerns	concern	NOUN
cana-6092	76	13	about	about	ADP
cana-6092	76	14	interpretability	interpretability	NOUN
cana-6092	76	15	and	and	CCONJ
cana-6092	76	16	trustworthiness	trustworthiness	NOUN
cana-6092	76	17	,	,	PUNCT
cana-6092	76	18	particularly	particularly	ADV
cana-6092	76	19	in	in	ADP
cana-6092	76	20	safety	safety	NOUN
cana-6092	76	21	-	-	PUNCT
cana-6092	76	22	critical	critical	ADJ
cana-6092	76	23	applications	application	NOUN
cana-6092	76	24	like	like	ADP
cana-6092	76	25	medical	medical	ADJ
cana-6092	76	26	diagnosis	diagnosis	NOUN
cana-6092	76	27	or	or	CCONJ
cana-6092	76	28	structural	structural	ADJ
cana-6092	76	29	design	design	NOUN
cana-6092	76	30	15	15	NUM
cana-6092	76	31	.	.	PUNCT
cana-6092	77	1	recent	recent	ADJ
cana-6092	77	2	work	work	NOUN
cana-6092	77	3	has	have	AUX
cana-6092	77	4	begun	begin	VERB
cana-6092	77	5	establishing	establish	VERB
cana-6092	77	6	theoretical	theoretical	ADJ
cana-6092	77	7	foundations	foundation	NOUN
cana-6092	77	8	for	for	ADP
cana-6092	77	9	neural	neural	ADJ
cana-6092	77	10	network	network	NOUN
cana-6092	77	11	-	-	PUNCT
cana-6092	77	12	based	base	VERB
cana-6092	77	13	inversion	inversion	NOUN
cana-6092	77	14	.	.	PUNCT
cana-6092	78	1	for	for	ADP
cana-6092	78	2	example	example	NOUN
cana-6092	78	3	,	,	PUNCT
cana-6092	78	4	analysis	analysis	NOUN
cana-6092	78	5	of	of	ADP
cana-6092	78	6	the	the	DET
cana-6092	78	7	stability	stability	NOUN
cana-6092	78	8	-	-	PUNCT
cana-6092	78	9	accuracy	accuracy	NOUN
cana-6092	78	10	trade	trade	NOUN
cana-6092	78	11	-	-	PUNCT
cana-6092	78	12	off	off	NOUN
cana-6092	78	13	provides	provide	VERB
cana-6092	78	14	insights	insight	NOUN
cana-6092	78	15	into	into	ADP
cana-6092	78	16	when	when	SCONJ
cana-6092	78	17	neural	neural	ADJ
cana-6092	78	18	networks	network	NOUN
cana-6092	78	19	are	be	AUX
cana-6092	78	20	likely	likely	ADJ
cana-6092	78	21	to	to	PART
cana-6092	78	22	succeed	succeed	VERB
cana-6092	78	23	or	or	CCONJ
cana-6092	78	24	fail	fail	VERB
cana-6092	78	25	1	1	NUM
cana-6092	78	26	.	.	PUNCT
cana-6092	79	1	however	however	ADV
cana-6092	79	2	,	,	PUNCT
cana-6092	79	3	further	further	ADJ
cana-6092	79	4	theoretical	theoretical	ADJ
cana-6092	79	5	development	development	NOUN
cana-6092	79	6	is	be	AUX
cana-6092	79	7	needed	need	VERB
cana-6092	79	8	to	to	PART
cana-6092	79	9	fully	fully	ADV
cana-6092	79	10	understand	understand	VERB
cana-6092	79	11	the	the	DET
cana-6092	79	12	properties	property	NOUN
cana-6092	79	13	and	and	CCONJ
cana-6092	79	14	limitations	limitation	NOUN
cana-6092	79	15	of	of	ADP
cana-6092	79	16	these	these	DET
cana-6092	79	17	approaches	approach	NOUN
cana-6092	79	18	,	,	PUNCT
cana-6092	79	19	especially	especially	ADV
cana-6092	79	20	for	for	ADP
cana-6092	79	21	nonlinear	nonlinear	ADJ
cana-6092	79	22	and	and	CCONJ
cana-6092	79	23	large	large	ADJ
cana-6092	79	24	-	-	PUNCT
cana-6092	79	25	scale	scale	NOUN
cana-6092	79	26	problems	problem	NOUN
cana-6092	79	27	1	1	NUM
cana-6092	79	28	.	.	X
cana-6092	79	29	5.2	5.2	NUM
cana-6092	79	30	data	datum	NOUN
cana-6092	79	31	requirements	requirement	NOUN
cana-6092	79	32	and	and	CCONJ
cana-6092	79	33	generalization	generalization	NOUN
cana-6092	79	34	neural	neural	ADJ
cana-6092	79	35	networks	network	NOUN
cana-6092	79	36	typically	typically	ADV
cana-6092	79	37	require	require	VERB
cana-6092	79	38	large	large	ADJ
cana-6092	79	39	training	training	NOUN
cana-6092	79	40	datasets	dataset	NOUN
cana-6092	79	41	to	to	PART
cana-6092	79	42	learn	learn	VERB
cana-6092	79	43	complex	complex	ADJ
cana-6092	79	44	distributions	distribution	NOUN
cana-6092	79	45	effectively	effectively	ADV
cana-6092	79	46	35	35	NUM
cana-6092	79	47	.	.	PUNCT
cana-6092	80	1	this	this	PRON
cana-6092	80	2	presents	present	VERB
cana-6092	80	3	challenges	challenge	NOUN
cana-6092	80	4	in	in	ADP
cana-6092	80	5	domains	domain	NOUN
cana-6092	80	6	where	where	SCONJ
cana-6092	80	7	data	datum	NOUN
cana-6092	80	8	is	be	AUX
cana-6092	80	9	scarce	scarce	ADJ
cana-6092	80	10	,	,	PUNCT
cana-6092	80	11	expensive	expensive	ADJ
cana-6092	80	12	to	to	PART
cana-6092	80	13	acquire	acquire	VERB
cana-6092	80	14	,	,	PUNCT
cana-6092	80	15	or	or	CCONJ
cana-6092	80	16	difficult	difficult	ADJ
cana-6092	80	17	to	to	PART
cana-6092	80	18	label	label	VERB
cana-6092	80	19	.	.	PUNCT
cana-6092	81	1	for	for	ADP
cana-6092	81	2	example	example	NOUN
cana-6092	81	3	,	,	PUNCT
cana-6092	81	4	in	in	ADP
cana-6092	81	5	medical	medical	ADJ
cana-6092	81	6	imaging	imaging	NOUN
cana-6092	81	7	,	,	PUNCT
cana-6092	81	8	high	high	ADJ
cana-6092	81	9	-	-	PUNCT
cana-6092	81	10	quality	quality	NOUN
cana-6092	81	11	labeled	label	VERB
cana-6092	81	12	datasets	dataset	NOUN
cana-6092	81	13	may	may	AUX
cana-6092	81	14	be	be	AUX
cana-6092	81	15	limited	limit	VERB
cana-6092	81	16	due	due	ADP
cana-6092	81	17	to	to	ADP
cana-6092	81	18	privacy	privacy	NOUN
cana-6092	81	19	concerns	concern	NOUN
cana-6092	81	20	or	or	CCONJ
cana-6092	81	21	annotation	annotation	NOUN
cana-6092	81	22	costs	cost	VERB
cana-6092	81	23	5	5	NUM
cana-6092	81	24	.	.	PUNCT
cana-6092	82	1	generalization	generalization	NOUN
cana-6092	82	2	beyond	beyond	ADP
cana-6092	82	3	the	the	DET
cana-6092	82	4	training	training	NOUN
cana-6092	82	5	distribution	distribution	NOUN
cana-6092	82	6	is	be	AUX
cana-6092	82	7	another	another	DET
cana-6092	82	8	significant	significant	ADJ
cana-6092	82	9	concern	concern	NOUN
cana-6092	82	10	.	.	PUNCT
cana-6092	83	1	neural	neural	ADJ
cana-6092	83	2	networks	network	NOUN
cana-6092	83	3	may	may	AUX
cana-6092	83	4	struggle	struggle	VERB
cana-6092	83	5	with	with	ADP
cana-6092	83	6	out	out	ADV
cana-6092	83	7	-	-	PUNCT
cana-6092	83	8	of	of	ADP
cana-6092	83	9	-	-	PUNCT
cana-6092	83	10	distribution	distribution	NOUN
cana-6092	83	11	inputs	input	NOUN
cana-6092	83	12	,	,	PUNCT
cana-6092	83	13	producing	produce	VERB
cana-6092	83	14	unrealistic	unrealistic	ADJ
cana-6092	83	15	or	or	CCONJ
cana-6092	83	16	inaccurate	inaccurate	ADJ
cana-6092	83	17	results	result	NOUN
cana-6092	83	18	when	when	SCONJ
cana-6092	83	19	presented	present	VERB
cana-6092	83	20	with	with	ADP
cana-6092	83	21	measurement	measurement	NOUN
cana-6092	83	22	data	datum	NOUN
cana-6092	83	23	that	that	PRON
cana-6092	83	24	differs	differ	VERB
cana-6092	83	25	substantially	substantially	ADV
cana-6092	83	26	from	from	ADP
cana-6092	83	27	training	train	VERB
cana-6092	83	28	examples	example	NOUN
cana-6092	83	29	13	13	NUM
cana-6092	83	30	.	.	PUNCT
cana-6092	84	1	this	this	DET
cana-6092	84	2	limitation	limitation	NOUN
cana-6092	84	3	is	be	AUX
cana-6092	84	4	particularly	particularly	ADV
cana-6092	84	5	problematic	problematic	ADJ
cana-6092	84	6	for	for	ADP
cana-6092	84	7	inverse	inverse	NOUN
cana-6092	84	8	problems	problem	NOUN
cana-6092	84	9	where	where	SCONJ
cana-6092	84	10	the	the	DET
cana-6092	84	11	measurement	measurement	NOUN
cana-6092	84	12	process	process	NOUN
cana-6092	84	13	may	may	AUX
cana-6092	84	14	vary	vary	VERB
cana-6092	84	15	or	or	CCONJ
cana-6092	84	16	where	where	SCONJ
cana-6092	84	17	novel	novel	ADJ
cana-6092	84	18	scenarios	scenario	NOUN
cana-6092	84	19	may	may	AUX
cana-6092	84	20	arise	arise	VERB
cana-6092	84	21	.	.	PUNCT
cana-6092	85	1	5.3	5.3	NUM
cana-6092	85	2	computational	computational	ADJ
cana-6092	85	3	complexity	complexity	NOUN
cana-6092	85	4	and	and	CCONJ
cana-6092	85	5	resource	resource	NOUN
cana-6092	85	6	requirements	requirement	NOUN
cana-6092	85	7	while	while	SCONJ
cana-6092	85	8	neural	neural	ADJ
cana-6092	85	9	networks	network	NOUN
cana-6092	85	10	can	can	AUX
cana-6092	85	11	accelerate	accelerate	VERB
cana-6092	85	12	inference	inference	NOUN
cana-6092	85	13	once	once	ADV
cana-6092	85	14	trained	train	VERB
cana-6092	85	15	,	,	PUNCT
cana-6092	85	16	the	the	DET
cana-6092	85	17	training	training	NOUN
cana-6092	85	18	process	process	NOUN
cana-6092	85	19	itself	itself	PRON
cana-6092	85	20	is	be	AUX
cana-6092	85	21	computationally	computationally	ADV
cana-6092	85	22	intensive	intensive	ADJ
cana-6092	85	23	,	,	PUNCT
cana-6092	85	24	requiring	require	VERB
cana-6092	85	25	substantial	substantial	ADJ
cana-6092	85	26	computational	computational	ADJ
cana-6092	85	27	resources	resource	NOUN
cana-6092	85	28	and	and	CCONJ
cana-6092	85	29	time	time	NOUN
cana-6092	85	30	34	34	NUM
cana-6092	85	31	.	.	PUNCT
cana-6092	86	1	for	for	ADP
cana-6092	86	2	large	large	ADJ
cana-6092	86	3	-	-	PUNCT
cana-6092	86	4	scale	scale	NOUN
cana-6092	86	5	problems	problem	NOUN
cana-6092	86	6	,	,	PUNCT
cana-6092	86	7	training	training	NOUN
cana-6092	86	8	may	may	AUX
cana-6092	86	9	require	require	VERB
cana-6092	86	10	days	day	NOUN
cana-6092	86	11	or	or	CCONJ
cana-6092	86	12	weeks	week	NOUN
cana-6092	86	13	on	on	ADP
cana-6092	86	14	specialized	specialized	ADJ
cana-6092	86	15	hardware	hardware	NOUN
cana-6092	86	16	,	,	PUNCT
cana-6092	86	17	limiting	limit	VERB
cana-6092	86	18	accessibility	accessibility	NOUN
cana-6092	86	19	for	for	ADP
cana-6092	86	20	some	some	DET
cana-6092	86	21	research	research	NOUN
cana-6092	86	22	groups	group	NOUN
cana-6092	86	23	and	and	CCONJ
cana-6092	86	24	applications	application	NOUN
cana-6092	86	25	4	4	NUM
cana-6092	86	26	.	.	PUNCT
cana-6092	87	1	the	the	DET
cana-6092	87	2	memory	memory	NOUN
cana-6092	87	3	requirements	requirement	NOUN
cana-6092	87	4	of	of	ADP
cana-6092	87	5	neural	neural	ADJ
cana-6092	87	6	network	network	NOUN
cana-6092	87	7	models	model	NOUN
cana-6092	87	8	can	can	AUX
cana-6092	87	9	also	also	ADV
cana-6092	87	10	be	be	AUX
cana-6092	87	11	significant	significant	ADJ
cana-6092	87	12	,	,	PUNCT
cana-6092	87	13	particularly	particularly	ADV
cana-6092	87	14	for	for	ADP
cana-6092	87	15	high	high	ADJ
cana-6092	87	16	-	-	PUNCT
cana-6092	87	17	dimensional	dimensional	ADJ
cana-6092	87	18	problems	problem	NOUN
cana-6092	87	19	.	.	PUNCT
cana-6092	88	1	as	as	SCONJ
cana-6092	88	2	network	network	NOUN
cana-6092	88	3	size	size	NOUN
cana-6092	88	4	grows	grow	VERB
cana-6092	88	5	to	to	PART
cana-6092	88	6	handle	handle	VERB
cana-6092	88	7	more	more	ADJ
cana-6092	88	8	complex	complex	ADJ
cana-6092	88	9	problems	problem	NOUN
cana-6092	88	10	,	,	PUNCT
cana-6092	88	11	memory	memory	NOUN
cana-6092	88	12	consumption	consumption	NOUN
cana-6092	88	13	may	may	AUX
cana-6092	88	14	become	become	VERB
cana-6092	88	15	a	a	DET
cana-6092	88	16	limiting	limit	VERB
cana-6092	88	17	factor	factor	NOUN
cana-6092	88	18	,	,	PUNCT
cana-6092	88	19	especially	especially	ADV
cana-6092	88	20	for	for	ADP
cana-6092	88	21	applications	application	NOUN
cana-6092	88	22	requiring	require	VERB
cana-6092	88	23	real	real	ADJ
cana-6092	88	24	-	-	PUNCT
cana-6092	88	25	time	time	NOUN
cana-6092	88	26	operation	operation	NOUN
cana-6092	88	27	on	on	ADP
cana-6092	88	28	embedded	embed	VERB
cana-6092	88	29	systems	system	NOUN
cana-6092	88	30	4	4	NUM
cana-6092	88	31	.	.	NOUN
cana-6092	88	32	5.4	5.4	NUM
cana-6092	88	33	integration	integration	NOUN
cana-6092	88	34	with	with	ADP
cana-6092	88	35	traditional	traditional	ADJ
cana-6092	88	36	methods	method	NOUN
cana-6092	88	37	fully	fully	ADV
cana-6092	88	38	replacing	replace	VERB
cana-6092	88	39	traditional	traditional	ADJ
cana-6092	88	40	inversion	inversion	NOUN
cana-6092	88	41	methods	method	NOUN
cana-6092	88	42	with	with	ADP
cana-6092	88	43	neural	neural	ADJ
cana-6092	88	44	networks	network	NOUN
cana-6092	88	45	may	may	AUX
cana-6092	88	46	not	not	PART
cana-6092	88	47	be	be	AUX
cana-6092	88	48	desirable	desirable	ADJ
cana-6092	88	49	or	or	CCONJ
cana-6092	88	50	practical	practical	ADJ
cana-6092	88	51	in	in	ADP
cana-6092	88	52	all	all	DET
cana-6092	88	53	applications	application	NOUN
cana-6092	88	54	15	15	NUM
cana-6092	88	55	.	.	PUNCT
cana-6092	89	1	hybrid	hybrid	ADJ
cana-6092	89	2	approaches	approach	NOUN
cana-6092	89	3	that	that	PRON
cana-6092	89	4	combine	combine	VERB
cana-6092	89	5	neural	neural	ADJ
cana-6092	89	6	networks	network	NOUN
cana-6092	89	7	with	with	ADP
cana-6092	89	8	traditional	traditional	ADJ
cana-6092	89	9	methods	method	NOUN
cana-6092	89	10	offer	offer	VERB
cana-6092	89	11	promising	promise	VERB
cana-6092	89	12	directions	direction	NOUN
cana-6092	89	13	but	but	CCONJ
cana-6092	89	14	introduce	introduce	VERB
cana-6092	89	15	challenges	challenge	NOUN
cana-6092	89	16	in	in	ADP
cana-6092	89	17	seamlessly	seamlessly	ADV
cana-6092	89	18	integrating	integrate	VERB
cana-6092	89	19	these	these	DET
cana-6092	89	20	different	different	ADJ
cana-6092	89	21	paradigms	paradigm	NOUN
cana-6092	89	22	17	17	NUM
cana-6092	89	23	.	.	PUNCT
cana-6092	90	1	for	for	ADP
cana-6092	90	2	example	example	NOUN
cana-6092	90	3	,	,	PUNCT
cana-6092	90	4	neural	neural	ADJ
cana-6092	90	5	networks	network	NOUN
cana-6092	90	6	can	can	AUX
cana-6092	90	7	be	be	AUX
cana-6092	90	8	used	use	VERB
cana-6092	90	9	to	to	PART
cana-6092	90	10	learn	learn	VERB
cana-6092	90	11	effective	effective	ADJ
cana-6092	90	12	regularizers	regularizer	NOUN
cana-6092	90	13	or	or	CCONJ
cana-6092	90	14	prior	prior	ADJ
cana-6092	90	15	distributions	distribution	NOUN
cana-6092	90	16	that	that	PRON
cana-6092	90	17	are	be	AUX
cana-6092	90	18	then	then	ADV
cana-6092	90	19	used	use	VERB
cana-6092	90	20	within	within	ADP
cana-6092	90	21	traditional	traditional	ADJ
cana-6092	90	22	optimization	optimization	NOUN
cana-6092	90	23	frameworks	framework	NOUN
cana-6092	90	24	17	17	NUM
cana-6092	90	25	.	.	PUNCT
cana-6092	91	1	however	however	ADV
cana-6092	91	2	,	,	PUNCT
cana-6092	91	3	designing	design	VERB
cana-6092	91	4	effective	effective	ADJ
cana-6092	91	5	hybrid	hybrid	ADJ
cana-6092	91	6	schemes	scheme	NOUN
cana-6092	91	7	requires	require	VERB
cana-6092	91	8	careful	careful	ADJ
cana-6092	91	9	consideration	consideration	NOUN
cana-6092	91	10	of	of	ADP
cana-6092	91	11	how	how	SCONJ
cana-6092	91	12	to	to	PART
cana-6092	91	13	leverage	leverage	VERB
cana-6092	91	14	the	the	DET
cana-6092	91	15	strengths	strength	NOUN
cana-6092	91	16	of	of	ADP
cana-6092	91	17	both	both	DET
cana-6092	91	18	approaches	approach	NOUN
cana-6092	91	19	while	while	SCONJ
cana-6092	91	20	mitigating	mitigate	VERB
cana-6092	91	21	their	their	PRON
cana-6092	91	22	weaknesses	weakness	NOUN
cana-6092	91	23	1	1	NUM
cana-6092	91	24	.	.	PUNCT
cana-6092	92	1	6.future	6.future	NUM
cana-6092	92	2	directions	direction	NOUN
cana-6092	92	3	6.1	6.1	NUM
cana-6092	92	4	integration	integration	NOUN
cana-6092	92	5	of	of	ADP
cana-6092	92	6	physical	physical	ADJ
cana-6092	92	7	models	model	NOUN
cana-6092	92	8	and	and	CCONJ
cana-6092	92	9	domain	domain	NOUN
cana-6092	92	10	knowledge	knowledge	NOUN
cana-6092	92	11	future	future	ADJ
cana-6092	92	12	research	research	NOUN
cana-6092	92	13	should	should	AUX
cana-6092	92	14	further	far	ADV
cana-6092	92	15	explore	explore	VERB
cana-6092	92	16	the	the	DET
cana-6092	92	17	integration	integration	NOUN
cana-6092	92	18	of	of	ADP
cana-6092	92	19	physical	physical	ADJ
cana-6092	92	20	knowledge	knowledge	NOUN
cana-6092	92	21	with	with	ADP
cana-6092	92	22	data	data	NOUN
cana-6092	92	23	-	-	PUNCT
cana-6092	92	24	driven	drive	VERB
cana-6092	92	25	neural	neural	ADJ
cana-6092	92	26	network	network	NOUN
cana-6092	92	27	approaches	approach	VERB
cana-6092	92	28	47	47	NUM
cana-6092	92	29	.	.	PUNCT
cana-6092	93	1	physics	physics	NOUN
cana-6092	93	2	-	-	PUNCT
cana-6092	93	3	informed	inform	VERB
cana-6092	93	4	neural	neural	ADJ
cana-6092	93	5	networks	network	NOUN
cana-6092	93	6	that	that	PRON
cana-6092	93	7	incorporate	incorporate	VERB
cana-6092	93	8	governing	govern	VERB
cana-6092	93	9	equations	equation	NOUN
cana-6092	93	10	,	,	PUNCT
cana-6092	93	11	boundary	boundary	ADJ
cana-6092	93	12	conditions	condition	NOUN
cana-6092	93	13	,	,	PUNCT
cana-6092	93	14	and	and	CCONJ
cana-6092	93	15	other	other	ADJ
cana-6092	93	16	physical	physical	ADJ
cana-6092	93	17	constraints	constraint	NOUN
cana-6092	93	18	can	can	AUX
cana-6092	93	19	improve	improve	VERB
cana-6092	93	20	generalization	generalization	NOUN
cana-6092	93	21	,	,	PUNCT
cana-6092	93	22	reduce	reduce	VERB
cana-6092	93	23	data	datum	NOUN
cana-6092	93	24	requirements	requirement	NOUN
cana-6092	93	25	,	,	PUNCT
cana-6092	93	26	and	and	CCONJ
cana-6092	93	27	enhance	enhance	VERB
cana-6092	93	28	the	the	DET
cana-6092	93	29	physical	physical	ADJ
cana-6092	93	30	plausibility	plausibility	NOUN
cana-6092	93	31	of	of	ADP
cana-6092	93	32	solutions	solution	NOUN
cana-6092	93	33	47	47	NUM
cana-6092	93	34	.	.	PUNCT
cana-6092	94	1	differentiable	differentiable	ADJ
cana-6092	94	2	simulations	simulation	NOUN
cana-6092	94	3	represent	represent	VERB
cana-6092	94	4	another	another	DET
cana-6092	94	5	promising	promising	ADJ
cana-6092	94	6	direction	direction	NOUN
cana-6092	94	7	,	,	PUNCT
cana-6092	94	8	enabling	enable	VERB
cana-6092	94	9	end	end	NOUN
cana-6092	94	10	-	-	PUNCT
cana-6092	94	11	to	to	ADP
cana-6092	94	12	-	-	PUNCT
cana-6092	94	13	end	end	NOUN
cana-6092	94	14	training	training	NOUN
cana-6092	94	15	of	of	ADP
cana-6092	94	16	networks	network	NOUN
cana-6092	94	17	that	that	PRON
cana-6092	94	18	respect	respect	VERB
cana-6092	94	19	physical	physical	ADJ
cana-6092	94	20	laws	law	NOUN
cana-6092	94	21	23	23	NUM
cana-6092	94	22	.	.	PUNCT
cana-6092	95	1	as	as	SCONJ
cana-6092	95	2	differentiable	differentiable	ADJ
cana-6092	95	3	simulations	simulation	NOUN
cana-6092	95	4	become	become	VERB
cana-6092	95	5	more	more	ADV
cana-6092	95	6	sophisticated	sophisticated	ADJ
cana-6092	95	7	and	and	CCONJ
cana-6092	95	8	efficient	efficient	ADJ
cana-6092	95	9	,	,	PUNCT
cana-6092	95	10	they	they	PRON
cana-6092	95	11	will	will	AUX
cana-6092	95	12	enable	enable	VERB
cana-6092	95	13	neural	neural	ADJ
cana-6092	95	14	networks	network	NOUN
cana-6092	95	15	to	to	PART
cana-6092	95	16	tackle	tackle	VERB
cana-6092	95	17	increasingly	increasingly	ADV
cana-6092	95	18	complex	complex	ADJ
cana-6092	95	19	inverse	inverse	NOUN
cana-6092	95	20	problems	problem	NOUN
cana-6092	95	21	while	while	SCONJ
cana-6092	95	22	maintaining	maintain	VERB
cana-6092	95	23	physical	physical	ADJ
cana-6092	95	24	consistency	consistency	NOUN
cana-6092	95	25	2	2	NUM
cana-6092	95	26	.	.	NOUN
cana-6092	95	27	6.2	6.2	NUM
cana-6092	95	28	theoretical	theoretical	ADJ
cana-6092	95	29	advances	advance	NOUN
cana-6092	95	30	and	and	CCONJ
cana-6092	95	31	uncertainty	uncertainty	NOUN
cana-6092	95	32	quantification	quantification	NOUN
cana-6092	95	33	strengthening	strengthen	VERB
cana-6092	95	34	the	the	DET
cana-6092	95	35	theoretical	theoretical	ADJ
cana-6092	95	36	foundations	foundation	NOUN
cana-6092	95	37	of	of	ADP
cana-6092	95	38	neural	neural	ADJ
cana-6092	95	39	network	network	NOUN
cana-6092	95	40	-	-	PUNCT
cana-6092	95	41	based	base	VERB
cana-6092	95	42	inversion	inversion	NOUN
cana-6092	95	43	should	should	AUX
cana-6092	95	44	be	be	AUX
cana-6092	95	45	a	a	DET
cana-6092	95	46	priority	priority	NOUN
cana-6092	95	47	1	1	NUM
cana-6092	95	48	.	.	PUNCT
cana-6092	96	1	this	this	PRON
cana-6092	96	2	includes	include	VERB
cana-6092	96	3	developing	develop	VERB
cana-6092	96	4	better	well	ADJ
cana-6092	96	5	understanding	understanding	NOUN
cana-6092	96	6	of	of	ADP
cana-6092	96	7	convergence	convergence	NOUN
cana-6092	96	8	properties	property	NOUN
cana-6092	96	9	,	,	PUNCT
cana-6092	96	10	generalization	generalization	NOUN
cana-6092	96	11	error	error	NOUN
cana-6092	96	12	bounds	bound	NOUN
cana-6092	96	13	,	,	PUNCT
cana-6092	96	14	and	and	CCONJ
cana-6092	96	15	conditions	condition	NOUN
cana-6092	96	16	for	for	ADP
cana-6092	96	17	uniqueness	uniqueness	NOUN
cana-6092	96	18	and	and	CCONJ
cana-6092	96	19	stability	stability	NOUN
cana-6092	96	20	of	of	ADP
cana-6092	96	21	solutions	solution	NOUN
cana-6092	96	22	1	1	NUM
cana-6092	96	23	.	.	PUNCT
cana-6092	96	24	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	PROPN
cana-6092	96	25	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	96	26	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	96	27	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	96	28	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	96	29	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	96	30	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	96	31	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	96	32	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	96	33	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	96	34	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	97	1	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	97	2	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	97	3	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	97	4	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	97	5	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	NOUN
cana-6092	97	6	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	NOUN
cana-6092	98	1	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	99	1	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	100	1	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	100	2	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	100	3	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	100	4	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	100	5	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	100	6	https://www.sciencedirect.com/science/article/pii/s0045782523006291	https://www.sciencedirect.com/science/article/pii/s0045782523006291	PROPN
cana-6092	100	7	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	PROPN
cana-6092	100	8	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	100	9	https://arxiv.org/abs/2408.08119	https://arxiv.org/abs/2408.08119	ADJ
cana-6092	100	10	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	101	1	https://arxiv.org/abs/2211.13692	https://arxiv.org/abs/2211.13692	VERB
cana-6092	101	2	communications	communication	NOUN
cana-6092	101	3	on	on	ADP
cana-6092	101	4	applied	apply	VERB
cana-6092	101	5	nonlinear	nonlinear	ADJ
cana-6092	101	6	analysis	analysis	NOUN
cana-6092	101	7	issn	issn	NOUN
cana-6092	101	8	:	:	PUNCT
cana-6092	101	9	1074	1074	NUM
cana-6092	101	10	-	-	PUNCT
cana-6092	101	11	133x	133x	NUM
cana-6092	101	12	vol	vol	NOUN
cana-6092	101	13	31	31	NUM
cana-6092	101	14	no	no	NOUN
cana-6092	101	15	.	.	NOUN
cana-6092	101	16	2	2	NUM
cana-6092	101	17	(	(	PUNCT
cana-6092	101	18	2024	2024	NUM
cana-6092	101	19	)	)	PUNCT
cana-6092	101	20	506	506	NUM
cana-6092	101	21	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-6092	101	22	improved	improve	VERB
cana-6092	101	23	methods	method	NOUN
cana-6092	101	24	for	for	ADP
cana-6092	101	25	uncertainty	uncertainty	NOUN
cana-6092	101	26	quantification	quantification	NOUN
cana-6092	101	27	are	be	AUX
cana-6092	101	28	essential	essential	ADJ
cana-6092	101	29	for	for	ADP
cana-6092	101	30	critical	critical	ADJ
cana-6092	101	31	applications	application	NOUN
cana-6092	101	32	where	where	SCONJ
cana-6092	101	33	understanding	understand	VERB
cana-6092	101	34	the	the	DET
cana-6092	101	35	reliability	reliability	NOUN
cana-6092	101	36	of	of	ADP
cana-6092	101	37	solutions	solution	NOUN
cana-6092	101	38	is	be	AUX
cana-6092	101	39	as	as	ADV
cana-6092	101	40	important	important	ADJ
cana-6092	101	41	as	as	ADP
cana-6092	101	42	the	the	DET
cana-6092	101	43	solutions	solution	NOUN
cana-6092	101	44	themselves	themselves	PRON
cana-6092	101	45	58	58	NUM
cana-6092	101	46	.	.	PUNCT
cana-6092	102	1	bayesian	bayesian	NOUN
cana-6092	102	2	neural	neural	ADJ
cana-6092	102	3	networks	network	NOUN
cana-6092	102	4	,	,	PUNCT
cana-6092	102	5	ensemble	ensemble	ADJ
cana-6092	102	6	methods	method	NOUN
cana-6092	102	7	,	,	PUNCT
cana-6092	102	8	and	and	CCONJ
cana-6092	102	9	probabilistic	probabilistic	ADJ
cana-6092	102	10	programming	programming	NOUN
cana-6092	102	11	approaches	approach	NOUN
cana-6092	102	12	offer	offer	VERB
cana-6092	102	13	promising	promising	ADJ
cana-6092	102	14	directions	direction	NOUN
cana-6092	102	15	for	for	ADP
cana-6092	102	16	uncertainty	uncertainty	NOUN
cana-6092	102	17	-	-	PUNCT
cana-6092	102	18	aware	aware	ADJ
cana-6092	102	19	inversion	inversion	NOUN
cana-6092	102	20	5	5	NUM
cana-6092	102	21	.	.	SYM
cana-6092	102	22	6.3	6.3	NUM
cana-6092	102	23	advanced	advanced	ADJ
cana-6092	102	24	architectures	architecture	NOUN
cana-6092	102	25	and	and	CCONJ
cana-6092	102	26	learning	learn	VERB
cana-6092	102	27	paradigms	paradigm	VERB
cana-6092	102	28	developing	develop	VERB
cana-6092	102	29	specialized	specialized	ADJ
cana-6092	102	30	architectures	architecture	NOUN
cana-6092	102	31	tailored	tailor	VERB
cana-6092	102	32	to	to	ADP
cana-6092	102	33	specific	specific	ADJ
cana-6092	102	34	inverse	inverse	NOUN
cana-6092	102	35	problem	problem	NOUN
cana-6092	102	36	characteristics	characteristic	NOUN
cana-6092	102	37	represents	represent	VERB
cana-6092	102	38	a	a	DET
cana-6092	102	39	promising	promising	ADJ
cana-6092	102	40	research	research	NOUN
cana-6092	102	41	direction	direction	NOUN
cana-6092	102	42	34	34	NUM
cana-6092	102	43	.	.	PUNCT
cana-6092	103	1	this	this	PRON
cana-6092	103	2	includes	include	VERB
cana-6092	103	3	architectures	architecture	NOUN
cana-6092	103	4	that	that	PRON
cana-6092	103	5	respect	respect	VERB
cana-6092	103	6	problem	problem	NOUN
cana-6092	103	7	-	-	PUNCT
cana-6092	103	8	specific	specific	ADJ
cana-6092	103	9	symmetries	symmetry	NOUN
cana-6092	103	10	,	,	PUNCT
cana-6092	103	11	handle	handle	VERB
cana-6092	103	12	multi	multi	ADJ
cana-6092	103	13	-	-	ADJ
cana-6092	103	14	modal	modal	ADJ
cana-6092	103	15	data	datum	NOUN
cana-6092	103	16	,	,	PUNCT
cana-6092	103	17	or	or	CCONJ
cana-6092	103	18	efficiently	efficiently	ADV
cana-6092	103	19	represent	represent	VERB
cana-6092	103	20	multi	multi	ADJ
cana-6092	103	21	-	-	ADJ
cana-6092	103	22	scale	scale	ADJ
cana-6092	103	23	features	feature	VERB
cana-6092	103	24	34	34	NUM
cana-6092	103	25	.	.	PUNCT
cana-6092	104	1	self	self	NOUN
cana-6092	104	2	-	-	PUNCT
cana-6092	104	3	supervised	supervise	VERB
cana-6092	104	4	and	and	CCONJ
cana-6092	104	5	unsupervised	unsupervised	ADJ
cana-6092	104	6	learning	learning	NOUN
cana-6092	104	7	approaches	approach	NOUN
cana-6092	104	8	could	could	AUX
cana-6092	104	9	reduce	reduce	VERB
cana-6092	104	10	reliance	reliance	NOUN
cana-6092	104	11	on	on	ADP
cana-6092	104	12	labeled	label	VERB
cana-6092	104	13	training	training	NOUN
cana-6092	104	14	data	datum	NOUN
cana-6092	104	15	,	,	PUNCT
cana-6092	104	16	which	which	PRON
cana-6092	104	17	is	be	AUX
cana-6092	104	18	particularly	particularly	ADV
cana-6092	104	19	valuable	valuable	ADJ
cana-6092	104	20	in	in	ADP
cana-6092	104	21	domains	domain	NOUN
cana-6092	104	22	where	where	SCONJ
cana-6092	104	23	labeled	label	VERB
cana-6092	104	24	data	datum	NOUN
cana-6092	104	25	is	be	AUX
cana-6092	104	26	scarce	scarce	ADJ
cana-6092	104	27	35	35	NUM
cana-6092	104	28	.	.	PUNCT
cana-6092	105	1	techniques	technique	NOUN
cana-6092	105	2	such	such	ADJ
cana-6092	105	3	as	as	ADP
cana-6092	105	4	contrastive	contrastive	ADJ
cana-6092	105	5	learning	learning	NOUN
cana-6092	105	6	,	,	PUNCT
cana-6092	105	7	generative	generative	ADJ
cana-6092	105	8	modeling	modeling	NOUN
cana-6092	105	9	,	,	PUNCT
cana-6092	105	10	and	and	CCONJ
cana-6092	105	11	reinforcement	reinforcement	NOUN
cana-6092	105	12	learning	learning	NOUN
cana-6092	105	13	offer	offer	VERB
cana-6092	105	14	potential	potential	ADJ
cana-6092	105	15	pathways	pathway	NOUN
cana-6092	105	16	for	for	ADP
cana-6092	105	17	learning	learn	VERB
cana-6092	105	18	from	from	ADP
cana-6092	105	19	unlabeled	unlabeled	ADJ
cana-6092	105	20	or	or	CCONJ
cana-6092	105	21	weakly	weakly	ADV
cana-6092	105	22	labeled	label	VERB
cana-6092	105	23	data	datum	NOUN
cana-6092	105	24	3	3	NUM
cana-6092	105	25	.	.	NOUN
cana-6092	105	26	6.4	6.4	NUM
cana-6092	105	27	scalability	scalability	NOUN
cana-6092	105	28	and	and	CCONJ
cana-6092	105	29	efficiency	efficiency	NOUN
cana-6092	105	30	improvements	improvement	NOUN
cana-6092	105	31	enhancing	enhance	VERB
cana-6092	105	32	the	the	DET
cana-6092	105	33	scalability	scalability	NOUN
cana-6092	105	34	of	of	ADP
cana-6092	105	35	neural	neural	ADJ
cana-6092	105	36	network	network	NOUN
cana-6092	105	37	approaches	approach	NOUN
cana-6092	105	38	to	to	ADP
cana-6092	105	39	extremely	extremely	ADV
cana-6092	105	40	high	high	ADJ
cana-6092	105	41	-	-	PUNCT
cana-6092	105	42	dimensional	dimensional	ADJ
cana-6092	105	43	problems	problem	NOUN
cana-6092	105	44	is	be	AUX
cana-6092	105	45	an	an	DET
cana-6092	105	46	important	important	ADJ
cana-6092	105	47	direction	direction	NOUN
cana-6092	105	48	34	34	NUM
cana-6092	105	49	.	.	PUNCT
cana-6092	106	1	this	this	PRON
cana-6092	106	2	includes	include	VERB
cana-6092	106	3	developing	develop	VERB
cana-6092	106	4	more	more	ADV
cana-6092	106	5	efficient	efficient	ADJ
cana-6092	106	6	architectures	architecture	NOUN
cana-6092	106	7	,	,	PUNCT
cana-6092	106	8	training	training	NOUN
cana-6092	106	9	strategies	strategy	NOUN
cana-6092	106	10	,	,	PUNCT
cana-6092	106	11	and	and	CCONJ
cana-6092	106	12	optimization	optimization	NOUN
cana-6092	106	13	techniques	technique	NOUN
cana-6092	106	14	that	that	PRON
cana-6092	106	15	reduce	reduce	VERB
cana-6092	106	16	computational	computational	ADJ
cana-6092	106	17	requirements	requirement	NOUN
cana-6092	106	18	while	while	SCONJ
cana-6092	106	19	maintaining	maintain	VERB
cana-6092	106	20	performance	performance	NOUN
cana-6092	106	21	34	34	NUM
cana-6092	106	22	.	.	PUNCT
cana-6092	106	23	model	model	NOUN
cana-6092	106	24	compression	compression	NOUN
cana-6092	106	25	and	and	CCONJ
cana-6092	106	26	knowledge	knowledge	NOUN
cana-6092	106	27	distillation	distillation	NOUN
cana-6092	106	28	techniques	technique	NOUN
cana-6092	106	29	could	could	AUX
cana-6092	106	30	make	make	VERB
cana-6092	106	31	neural	neural	ADJ
cana-6092	106	32	network	network	NOUN
cana-6092	106	33	approaches	approach	VERB
cana-6092	106	34	more	more	ADV
cana-6092	106	35	accessible	accessible	ADJ
cana-6092	106	36	for	for	ADP
cana-6092	106	37	applications	application	NOUN
cana-6092	106	38	with	with	ADP
cana-6092	106	39	limited	limited	ADJ
cana-6092	106	40	computational	computational	ADJ
cana-6092	106	41	resources	resource	NOUN
cana-6092	106	42	or	or	CCONJ
cana-6092	106	43	real	real	ADJ
cana-6092	106	44	-	-	PUNCT
cana-6092	106	45	time	time	NOUN
cana-6092	106	46	requirements	requirement	NOUN
cana-6092	106	47	4	4	NUM
cana-6092	106	48	.	.	PUNCT
cana-6092	107	1	these	these	DET
cana-6092	107	2	techniques	technique	NOUN
cana-6092	107	3	aim	aim	VERB
cana-6092	107	4	to	to	PART
cana-6092	107	5	reduce	reduce	VERB
cana-6092	107	6	the	the	DET
cana-6092	107	7	size	size	NOUN
cana-6092	107	8	and	and	CCONJ
cana-6092	107	9	computational	computational	ADJ
cana-6092	107	10	requirements	requirement	NOUN
cana-6092	107	11	of	of	ADP
cana-6092	107	12	trained	train	VERB
cana-6092	107	13	models	model	NOUN
cana-6092	107	14	without	without	ADP
cana-6092	107	15	significant	significant	ADJ
cana-6092	107	16	performance	performance	NOUN
cana-6092	107	17	degradation	degradation	NOUN
cana-6092	107	18	4	4	NUM
cana-6092	107	19	.	.	PUNCT
cana-6092	108	1	7.conclusion	7.conclusion	NUM
cana-6092	108	2	neural	neural	ADJ
cana-6092	108	3	network	network	NOUN
cana-6092	108	4	-	-	PUNCT
cana-6092	108	5	based	base	VERB
cana-6092	108	6	approaches	approach	NOUN
cana-6092	108	7	have	have	AUX
cana-6092	108	8	emerged	emerge	VERB
cana-6092	108	9	as	as	ADP
cana-6092	108	10	powerful	powerful	ADJ
cana-6092	108	11	frameworks	framework	NOUN
cana-6092	108	12	for	for	ADP
cana-6092	108	13	solving	solve	VERB
cana-6092	108	14	large	large	ADJ
cana-6092	108	15	-	-	PUNCT
cana-6092	108	16	scale	scale	NOUN
cana-6092	108	17	inverse	inverse	NOUN
cana-6092	108	18	problems	problem	NOUN
cana-6092	108	19	across	across	ADP
cana-6092	108	20	diverse	diverse	ADJ
cana-6092	108	21	scientific	scientific	ADJ
cana-6092	108	22	and	and	CCONJ
cana-6092	108	23	engineering	engineering	NOUN
cana-6092	108	24	domains	domain	NOUN
cana-6092	108	25	.	.	PUNCT
cana-6092	109	1	by	by	ADP
cana-6092	109	2	leveraging	leverage	VERB
cana-6092	109	3	the	the	DET
cana-6092	109	4	universal	universal	ADJ
cana-6092	109	5	approximation	approximation	NOUN
cana-6092	109	6	capabilities	capability	NOUN
cana-6092	109	7	of	of	ADP
cana-6092	109	8	deep	deep	ADJ
cana-6092	109	9	networks	network	NOUN
cana-6092	109	10	,	,	PUNCT
cana-6092	109	11	these	these	DET
cana-6092	109	12	approaches	approach	NOUN
cana-6092	109	13	can	can	AUX
cana-6092	109	14	learn	learn	VERB
cana-6092	109	15	complex	complex	ADJ
cana-6092	109	16	prior	prior	ADJ
cana-6092	109	17	distributions	distribution	NOUN
cana-6092	109	18	from	from	ADP
cana-6092	109	19	data	datum	NOUN
cana-6092	109	20	,	,	PUNCT
cana-6092	109	21	enable	enable	VERB
cana-6092	109	22	rapid	rapid	ADJ
cana-6092	109	23	parameter	parameter	NOUN
cana-6092	109	24	estimation	estimation	NOUN
cana-6092	109	25	,	,	PUNCT
cana-6092	109	26	and	and	CCONJ
cana-6092	109	27	produce	produce	VERB
cana-6092	109	28	high	high	ADJ
cana-6092	109	29	-	-	PUNCT
cana-6092	109	30	fidelity	fidelity	NOUN
cana-6092	109	31	reconstructions	reconstruction	NOUN
cana-6092	109	32	while	while	SCONJ
cana-6092	109	33	significantly	significantly	ADV
cana-6092	109	34	reducing	reduce	VERB
cana-6092	109	35	computational	computational	ADJ
cana-6092	109	36	burden	burden	NOUN
cana-6092	109	37	compared	compare	VERB
cana-6092	109	38	to	to	ADP
cana-6092	109	39	traditional	traditional	ADJ
cana-6092	109	40	methods	method	NOUN
cana-6092	109	41	.	.	PUNCT
cana-6092	110	1	this	this	DET
cana-6092	110	2	paper	paper	NOUN
cana-6092	110	3	has	have	AUX
cana-6092	110	4	presented	present	VERB
cana-6092	110	5	a	a	DET
cana-6092	110	6	comprehensive	comprehensive	ADJ
cana-6092	110	7	framework	framework	NOUN
cana-6092	110	8	that	that	PRON
cana-6092	110	9	incorporates	incorporate	VERB
cana-6092	110	10	various	various	ADJ
cana-6092	110	11	neural	neural	ADJ
cana-6092	110	12	network	network	NOUN
cana-6092	110	13	architectures	architecture	NOUN
cana-6092	110	14	,	,	PUNCT
cana-6092	110	15	including	include	VERB
cana-6092	110	16	physics	physics	NOUN
cana-6092	110	17	-	-	PUNCT
cana-6092	110	18	informed	inform	VERB
cana-6092	110	19	neural	neural	ADJ
cana-6092	110	20	networks	network	NOUN
cana-6092	110	21	,	,	PUNCT
cana-6092	110	22	generative	generative	ADJ
cana-6092	110	23	adversarial	adversarial	ADJ
cana-6092	110	24	networks	network	NOUN
cana-6092	110	25	,	,	PUNCT
cana-6092	110	26	and	and	CCONJ
cana-6092	110	27	differentiable	differentiable	ADJ
cana-6092	110	28	simulation	simulation	NOUN
cana-6092	110	29	approaches	approach	NOUN
cana-6092	110	30	.	.	PUNCT
cana-6092	111	1	through	through	ADP
cana-6092	111	2	analysis	analysis	NOUN
cana-6092	111	3	of	of	ADP
cana-6092	111	4	applications	application	NOUN
cana-6092	111	5	in	in	ADP
cana-6092	111	6	medical	medical	ADJ
cana-6092	111	7	imaging	imaging	NOUN
cana-6092	111	8	,	,	PUNCT
cana-6092	111	9	geophysical	geophysical	ADJ
cana-6092	111	10	inversion	inversion	NOUN
cana-6092	111	11	,	,	PUNCT
cana-6092	111	12	and	and	CCONJ
cana-6092	111	13	pde	pde	NOUN
cana-6092	111	14	-	-	PUNCT
cana-6092	111	15	based	base	VERB
cana-6092	111	16	problems	problem	NOUN
cana-6092	111	17	,	,	PUNCT
cana-6092	111	18	we	we	PRON
cana-6092	111	19	have	have	AUX
cana-6092	111	20	demonstrated	demonstrate	VERB
cana-6092	111	21	that	that	SCONJ
cana-6092	111	22	neural	neural	ADJ
cana-6092	111	23	network	network	NOUN
cana-6092	111	24	methods	method	NOUN
cana-6092	111	25	can	can	AUX
cana-6092	111	26	achieve	achieve	VERB
cana-6092	111	27	superior	superior	ADJ
cana-6092	111	28	performance	performance	NOUN
cana-6092	111	29	compared	compare	VERB
cana-6092	111	30	to	to	ADP
cana-6092	111	31	traditional	traditional	ADJ
cana-6092	111	32	optimization	optimization	NOUN
cana-6092	111	33	methods	method	NOUN
cana-6092	111	34	,	,	PUNCT
cana-6092	111	35	particularly	particularly	ADV
cana-6092	111	36	for	for	ADP
cana-6092	111	37	problems	problem	NOUN
cana-6092	111	38	with	with	ADP
cana-6092	111	39	local	local	ADJ
cana-6092	111	40	minima	minima	NOUN
cana-6092	111	41	,	,	PUNCT
cana-6092	111	42	chaotic	chaotic	ADJ
cana-6092	111	43	behavior	behavior	NOUN
cana-6092	111	44	,	,	PUNCT
cana-6092	111	45	or	or	CCONJ
cana-6092	111	46	zero	zero	NUM
cana-6092	111	47	-	-	PUNCT
cana-6092	111	48	gradient	gradient	NOUN
cana-6092	111	49	regions	region	NOUN
cana-6092	111	50	.	.	PUNCT
cana-6092	112	1	despite	despite	SCONJ
cana-6092	112	2	significant	significant	ADJ
cana-6092	112	3	progress	progress	NOUN
cana-6092	112	4	,	,	PUNCT
cana-6092	112	5	important	important	ADJ
cana-6092	112	6	challenges	challenge	NOUN
cana-6092	112	7	remain	remain	VERB
cana-6092	112	8	regarding	regard	VERB
cana-6092	112	9	theoretical	theoretical	ADJ
cana-6092	112	10	guarantees	guarantee	NOUN
cana-6092	112	11	,	,	PUNCT
cana-6092	112	12	data	datum	NOUN
cana-6092	112	13	requirements	requirement	NOUN
cana-6092	112	14	,	,	PUNCT
cana-6092	112	15	computational	computational	ADJ
cana-6092	112	16	complexity	complexity	NOUN
cana-6092	112	17	,	,	PUNCT
cana-6092	112	18	and	and	CCONJ
cana-6092	112	19	integration	integration	NOUN
cana-6092	112	20	with	with	ADP
cana-6092	112	21	traditional	traditional	ADJ
cana-6092	112	22	methods	method	NOUN
cana-6092	112	23	.	.	PUNCT
cana-6092	113	1	future	future	ADJ
cana-6092	113	2	research	research	NOUN
cana-6092	113	3	should	should	AUX
cana-6092	113	4	focus	focus	VERB
cana-6092	113	5	on	on	ADP
cana-6092	113	6	strengthening	strengthen	VERB
cana-6092	113	7	theoretical	theoretical	ADJ
cana-6092	113	8	foundations	foundation	NOUN
cana-6092	113	9	,	,	PUNCT
cana-6092	113	10	improving	improve	VERB
cana-6092	113	11	uncertainty	uncertainty	NOUN
cana-6092	113	12	quantification	quantification	NOUN
cana-6092	113	13	,	,	PUNCT
cana-6092	113	14	developing	develop	VERB
cana-6092	113	15	specialized	specialized	ADJ
cana-6092	113	16	architectures	architecture	NOUN
cana-6092	113	17	,	,	PUNCT
cana-6092	113	18	and	and	CCONJ
cana-6092	113	19	enhancing	enhance	VERB
cana-6092	113	20	scalability	scalability	NOUN
cana-6092	113	21	and	and	CCONJ
cana-6092	113	22	efficiency	efficiency	NOUN
cana-6092	113	23	.	.	PUNCT
cana-6092	114	1	as	as	SCONJ
cana-6092	114	2	neural	neural	ADJ
cana-6092	114	3	network	network	NOUN
cana-6092	114	4	methodologies	methodology	NOUN
cana-6092	114	5	continue	continue	VERB
cana-6092	114	6	to	to	PART
cana-6092	114	7	evolve	evolve	VERB
cana-6092	114	8	and	and	CCONJ
cana-6092	114	9	integrate	integrate	VERB
cana-6092	114	10	with	with	ADP
cana-6092	114	11	complementary	complementary	ADJ
cana-6092	114	12	techniques	technique	NOUN
cana-6092	114	13	from	from	ADP
cana-6092	114	14	numerical	numerical	ADJ
cana-6092	114	15	computation	computation	NOUN
cana-6092	114	16	and	and	CCONJ
cana-6092	114	17	domain	domain	NOUN
cana-6092	114	18	sciences	science	NOUN
cana-6092	114	19	,	,	PUNCT
cana-6092	114	20	they	they	PRON
cana-6092	114	21	hold	hold	VERB
cana-6092	114	22	immense	immense	ADJ
cana-6092	114	23	potential	potential	NOUN
cana-6092	114	24	to	to	PART
cana-6092	114	25	transform	transform	VERB
cana-6092	114	26	inverse	inverse	ADJ
cana-6092	114	27	problem	problem	NOUN
cana-6092	114	28	solving	solve	VERB
cana-6092	114	29	across	across	ADP
cana-6092	114	30	scientific	scientific	ADJ
cana-6092	114	31	disciplines	discipline	NOUN
cana-6092	114	32	,	,	PUNCT
cana-6092	114	33	enabling	enable	VERB
cana-6092	114	34	new	new	ADJ
cana-6092	114	35	applications	application	NOUN
cana-6092	114	36	that	that	PRON
cana-6092	114	37	require	require	VERB
cana-6092	114	38	real	real	ADJ
cana-6092	114	39	-	-	PUNCT
cana-6092	114	40	time	time	NOUN
cana-6092	114	41	solutions	solution	NOUN
cana-6092	114	42	,	,	PUNCT
cana-6092	114	43	handle	handle	VERB
cana-6092	114	44	complex	complex	ADJ
cana-6092	114	45	uncertainties	uncertainty	NOUN
cana-6092	114	46	,	,	PUNCT
cana-6092	114	47	or	or	CCONJ
cana-6092	114	48	explore	explore	VERB
cana-6092	114	49	previously	previously	ADV
cana-6092	114	50	intractable	intractable	ADJ
cana-6092	114	51	problem	problem	NOUN
cana-6092	114	52	scales	scale	NOUN
cana-6092	114	53	.	.	PUNCT
cana-6092	115	1	references	reference	NOUN
cana-6092	115	2	1	1	NUM
cana-6092	115	3	.	.	PUNCT
cana-6092	116	1	hadamard	hadamard	PROPN
cana-6092	116	2	,	,	PUNCT
cana-6092	116	3	j.	j.	PROPN
cana-6092	116	4	(	(	PUNCT
cana-6092	116	5	1923	1923	NUM
cana-6092	116	6	)	)	PUNCT
cana-6092	116	7	.	.	PUNCT
cana-6092	117	1	lectures	lecture	NOUN
cana-6092	117	2	on	on	ADP
cana-6092	117	3	the	the	DET
cana-6092	117	4	cauchy	cauchy	ADJ
cana-6092	117	5	problem	problem	NOUN
cana-6092	117	6	in	in	ADP
cana-6092	117	7	linear	linear	ADJ
cana-6092	117	8	partial	partial	ADJ
cana-6092	117	9	differential	differential	NOUN
cana-6092	117	10	equations	equation	NOUN
cana-6092	117	11	.	.	PUNCT
cana-6092	118	1	yale	yale	PROPN
cana-6092	118	2	university	university	PROPN
cana-6092	118	3	press	press	NOUN
cana-6092	118	4	.	.	PUNCT
cana-6092	119	1	2	2	X
cana-6092	119	2	.	.	X
cana-6092	119	3	tarantola	tarantola	PROPN
cana-6092	119	4	,	,	PUNCT
cana-6092	119	5	a.	a.	NOUN
cana-6092	119	6	(	(	PUNCT
cana-6092	119	7	2005	2005	NUM
cana-6092	119	8	)	)	PUNCT
cana-6092	119	9	.	.	PUNCT
cana-6092	120	1	inverse	inverse	ADJ
cana-6092	120	2	problem	problem	NOUN
cana-6092	120	3	theory	theory	NOUN
cana-6092	120	4	and	and	CCONJ
cana-6092	120	5	methods	method	NOUN
cana-6092	120	6	for	for	ADP
cana-6092	120	7	model	model	NOUN
cana-6092	120	8	parameter	parameter	PROPN
cana-6092	120	9	estimation	estimation	PROPN
cana-6092	120	10	.	.	PUNCT
cana-6092	121	1	siam	siam	PROPN
cana-6092	121	2	.	.	PUNCT
cana-6092	122	1	3	3	X
cana-6092	122	2	.	.	X
cana-6092	122	3	engl	engl	PROPN
cana-6092	122	4	,	,	PUNCT
cana-6092	122	5	h.	h.	PROPN
cana-6092	122	6	w.	w.	PROPN
cana-6092	122	7	,	,	PUNCT
cana-6092	122	8	hanke	hanke	PROPN
cana-6092	122	9	,	,	PUNCT
cana-6092	122	10	m.	m.	NOUN
cana-6092	122	11	,	,	PUNCT
cana-6092	122	12	&	&	CCONJ
cana-6092	122	13	neubauer	neubauer	PROPN
cana-6092	122	14	,	,	PUNCT
cana-6092	122	15	a.	a.	NOUN
cana-6092	122	16	(	(	PUNCT
cana-6092	122	17	1996	1996	NUM
cana-6092	122	18	)	)	PUNCT
cana-6092	122	19	.	.	PUNCT
cana-6092	123	1	regularization	regularization	NOUN
cana-6092	123	2	of	of	ADP
cana-6092	123	3	inverse	inverse	NOUN
cana-6092	123	4	problems	problem	NOUN
cana-6092	123	5	.	.	PUNCT
cana-6092	124	1	kluwer	kluwer	NOUN
cana-6092	124	2	academic	academic	ADJ
cana-6092	124	3	publishers	publisher	NOUN
cana-6092	124	4	.	.	PUNCT
cana-6092	125	1	4	4	X
cana-6092	125	2	.	.	X
cana-6092	125	3	goodfellow	goodfellow	PROPN
cana-6092	125	4	,	,	PUNCT
cana-6092	125	5	i.	i.	PROPN
cana-6092	125	6	,	,	PUNCT
cana-6092	125	7	bengio	bengio	PROPN
cana-6092	125	8	,	,	PUNCT
cana-6092	125	9	y.	y.	PROPN
cana-6092	125	10	,	,	PUNCT
cana-6092	125	11	&	&	CCONJ
cana-6092	125	12	courville	courville	PROPN
cana-6092	125	13	,	,	PUNCT
cana-6092	125	14	a.	a.	NOUN
cana-6092	125	15	(	(	PUNCT
cana-6092	125	16	2016	2016	NUM
cana-6092	125	17	)	)	PUNCT
cana-6092	125	18	.	.	PUNCT
cana-6092	126	1	deep	deep	ADJ
cana-6092	126	2	learning	learning	NOUN
cana-6092	126	3	.	.	PUNCT
cana-6092	127	1	mit	mit	PROPN
cana-6092	127	2	press	press	NOUN
cana-6092	127	3	.	.	PUNCT
cana-6092	128	1	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	128	2	https://maths4dl.ac.uk/newsevents/maths4dl-conference-on-inverse-problems-and-deep-learning	https://maths4dl.ac.uk/newsevents/maths4dl-conference-on-inverse-problems-and-deep-learning	PROPN
cana-6092	128	3	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	128	4	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	128	5	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	128	6	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	128	7	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	128	8	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	128	9	https://link.springer.com/collections/jbbecebeha	https://link.springer.com/collections/jbbecebeha	PROPN
cana-6092	128	10	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	PROPN
cana-6092	128	11	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	128	12	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	128	13	https://arxiv.org/html/2408.08119v1	https://arxiv.org/html/2408.08119v1	NOUN
cana-6092	128	14	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	128	15	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	128	16	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	https://www.aimsciences.org/article/doi/10.3934/nhm.2020011	PROPN
cana-6092	128	17	communications	communication	NOUN
cana-6092	128	18	on	on	ADP
cana-6092	128	19	applied	apply	VERB
cana-6092	128	20	nonlinear	nonlinear	ADJ
cana-6092	128	21	analysis	analysis	NOUN
cana-6092	128	22	issn	issn	NOUN
cana-6092	128	23	:	:	PUNCT
cana-6092	128	24	1074	1074	NUM
cana-6092	128	25	-	-	PUNCT
cana-6092	128	26	133x	133x	NUM
cana-6092	128	27	vol	vol	NOUN
cana-6092	128	28	31	31	NUM
cana-6092	128	29	no	no	NOUN
cana-6092	128	30	.	.	NOUN
cana-6092	128	31	2	2	NUM
cana-6092	128	32	(	(	PUNCT
cana-6092	128	33	2024	2024	NUM
cana-6092	128	34	)	)	PUNCT
cana-6092	128	35	507	507	NUM
cana-6092	128	36	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	128	37	5	5	NUM
cana-6092	128	38	.	.	X
cana-6092	128	39	arridge	arridge	PROPN
cana-6092	128	40	,	,	PUNCT
cana-6092	128	41	s.	s.	PROPN
cana-6092	128	42	,	,	PUNCT
cana-6092	128	43	maass	maass	PROPN
cana-6092	128	44	,	,	PUNCT
cana-6092	128	45	p.	p.	PROPN
cana-6092	128	46	,	,	PUNCT
cana-6092	128	47	öktem	öktem	PROPN
cana-6092	128	48	,	,	PUNCT
cana-6092	128	49	o.	o.	PROPN
cana-6092	128	50	,	,	PUNCT
cana-6092	128	51	&	&	CCONJ
cana-6092	128	52	schönlieb	schönlieb	PROPN
cana-6092	128	53	,	,	PUNCT
cana-6092	128	54	c.-b	c.-b	PROPN
cana-6092	128	55	.	.	PROPN
cana-6092	129	1	(	(	PUNCT
cana-6092	129	2	2019	2019	NUM
cana-6092	129	3	)	)	PUNCT
cana-6092	129	4	.	.	PUNCT
cana-6092	130	1	solving	solve	VERB
cana-6092	130	2	inverse	inverse	NOUN
cana-6092	130	3	problems	problem	NOUN
cana-6092	130	4	using	use	VERB
cana-6092	130	5	data	data	NOUN
cana-6092	130	6	-	-	PUNCT
cana-6092	130	7	driven	drive	VERB
cana-6092	130	8	models	model	NOUN
cana-6092	130	9	.	.	PUNCT
cana-6092	131	1	acta	acta	PROPN
cana-6092	131	2	numerica	numerica	PROPN
cana-6092	131	3	,	,	PUNCT
cana-6092	131	4	28	28	NUM
cana-6092	131	5	,	,	PUNCT
cana-6092	131	6	1–174	1–174	NUM
cana-6092	131	7	.	.	PROPN
cana-6092	132	1	6	6	NUM
cana-6092	132	2	.	.	X
cana-6092	132	3	mccann	mccann	PROPN
cana-6092	132	4	,	,	PUNCT
cana-6092	132	5	m.	m.	NOUN
cana-6092	132	6	t.	t.	PROPN
cana-6092	132	7	,	,	PUNCT
cana-6092	132	8	jin	jin	PROPN
cana-6092	132	9	,	,	PUNCT
cana-6092	132	10	k.	k.	PROPN
cana-6092	132	11	h.	h.	PROPN
cana-6092	132	12	,	,	PUNCT
cana-6092	132	13	&	&	CCONJ
cana-6092	132	14	unser	unser	PROPN
cana-6092	132	15	,	,	PUNCT
cana-6092	132	16	m.	m.	NOUN
cana-6092	132	17	(	(	PUNCT
cana-6092	132	18	2017	2017	NUM
cana-6092	132	19	)	)	PUNCT
cana-6092	132	20	.	.	PUNCT
cana-6092	133	1	convolutional	convolutional	ADJ
cana-6092	133	2	neural	neural	ADJ
cana-6092	133	3	networks	network	NOUN
cana-6092	133	4	for	for	ADP
cana-6092	133	5	inverse	inverse	NOUN
cana-6092	133	6	problems	problem	NOUN
cana-6092	133	7	in	in	ADP
cana-6092	133	8	imaging	imaging	PROPN
cana-6092	133	9	:	:	PUNCT
cana-6092	133	10	a	a	DET
cana-6092	133	11	review	review	NOUN
cana-6092	133	12	.	.	PUNCT
cana-6092	134	1	ieee	ieee	NOUN
cana-6092	134	2	signal	signal	PROPN
cana-6092	134	3	processing	processing	NOUN
cana-6092	134	4	magazine	magazine	NOUN
cana-6092	134	5	,	,	PUNCT
cana-6092	134	6	34(6	34(6	NOUN
cana-6092	134	7	)	)	PUNCT
cana-6092	134	8	,	,	PUNCT
cana-6092	134	9	85–95	85–95	NUM
cana-6092	134	10	.	.	PUNCT
cana-6092	135	1	7	7	X
cana-6092	135	2	.	.	NOUN
cana-6092	135	3	raissi	raissi	ADJ
cana-6092	135	4	,	,	PUNCT
cana-6092	135	5	m.	m.	NOUN
cana-6092	135	6	,	,	PUNCT
cana-6092	135	7	perdikaris	perdikaris	NOUN
cana-6092	135	8	,	,	PUNCT
cana-6092	135	9	p.	p.	NOUN
cana-6092	135	10	,	,	PUNCT
cana-6092	135	11	&	&	CCONJ
cana-6092	135	12	karniadakis	karniadakis	PROPN
cana-6092	135	13	,	,	PUNCT
cana-6092	135	14	g.	g.	PROPN
cana-6092	135	15	e.	e.	PROPN
cana-6092	135	16	(	(	PUNCT
cana-6092	135	17	2019	2019	NUM
cana-6092	135	18	)	)	PUNCT
cana-6092	135	19	.	.	PUNCT
cana-6092	136	1	physics	physics	NOUN
cana-6092	136	2	-	-	PUNCT
cana-6092	136	3	informed	inform	VERB
cana-6092	136	4	neural	neural	ADJ
cana-6092	136	5	networks	network	NOUN
cana-6092	136	6	:	:	PUNCT
cana-6092	136	7	a	a	DET
cana-6092	136	8	deep	deep	ADJ
cana-6092	136	9	learning	learning	NOUN
cana-6092	136	10	framework	framework	NOUN
cana-6092	136	11	for	for	ADP
cana-6092	136	12	solving	solve	VERB
cana-6092	136	13	forward	forward	ADV
cana-6092	136	14	and	and	CCONJ
cana-6092	136	15	inverse	inverse	NOUN
cana-6092	136	16	problems	problem	NOUN
cana-6092	136	17	involving	involve	VERB
cana-6092	136	18	nonlinear	nonlinear	ADJ
cana-6092	136	19	partial	partial	ADJ
cana-6092	136	20	differential	differential	NOUN
cana-6092	136	21	equations	equation	NOUN
cana-6092	136	22	.	.	PUNCT
cana-6092	137	1	journal	journal	NOUN
cana-6092	137	2	of	of	ADP
cana-6092	137	3	computational	computational	ADJ
cana-6092	137	4	physics	physics	NOUN
cana-6092	137	5	,	,	PUNCT
cana-6092	137	6	378	378	NUM
cana-6092	137	7	,	,	PUNCT
cana-6092	137	8	686–707	686–707	NUM
cana-6092	137	9	.	.	NOUN
cana-6092	137	10	8	8	NUM
cana-6092	137	11	.	.	X
cana-6092	138	1	ronneberger	ronneberger	NOUN
cana-6092	138	2	,	,	PUNCT
cana-6092	138	3	o.	o.	PROPN
cana-6092	138	4	,	,	PUNCT
cana-6092	138	5	fischer	fischer	PROPN
cana-6092	138	6	,	,	PUNCT
cana-6092	138	7	p.	p.	PROPN
cana-6092	138	8	,	,	PUNCT
cana-6092	138	9	&	&	CCONJ
cana-6092	138	10	brox	brox	PROPN
cana-6092	138	11	,	,	PUNCT
cana-6092	138	12	t.	t.	PROPN
cana-6092	138	13	(	(	PUNCT
cana-6092	138	14	2015	2015	NUM
cana-6092	138	15	)	)	PUNCT
cana-6092	138	16	.	.	PUNCT
cana-6092	139	1	u	u	NOUN
cana-6092	139	2	-	-	NOUN
cana-6092	139	3	net	net	ADJ
cana-6092	139	4	:	:	PUNCT
cana-6092	139	5	convolutional	convolutional	ADJ
cana-6092	139	6	networks	network	NOUN
cana-6092	139	7	for	for	ADP
cana-6092	139	8	biomedical	biomedical	ADJ
cana-6092	139	9	image	image	NOUN
cana-6092	139	10	segmentation	segmentation	NOUN
cana-6092	139	11	.	.	PUNCT
cana-6092	140	1	in	in	ADP
cana-6092	140	2	international	international	ADJ
cana-6092	140	3	conference	conference	NOUN
cana-6092	140	4	on	on	ADP
cana-6092	140	5	medical	medical	ADJ
cana-6092	140	6	image	image	NOUN
cana-6092	140	7	computing	computing	NOUN
cana-6092	140	8	and	and	CCONJ
cana-6092	140	9	computer	computer	NOUN
cana-6092	140	10	-	-	PUNCT
cana-6092	140	11	assisted	assist	VERB
cana-6092	140	12	intervention	intervention	NOUN
cana-6092	140	13	(	(	PUNCT
cana-6092	140	14	pp	pp	ADJ
cana-6092	140	15	.	.	PUNCT
cana-6092	141	1	234–241	234–241	NUM
cana-6092	141	2	)	)	PUNCT
cana-6092	141	3	.	.	PUNCT
cana-6092	142	1	springer	springer	NOUN
cana-6092	142	2	.	.	PUNCT
cana-6092	143	1	9	9	X
cana-6092	143	2	.	.	X
cana-6092	144	1	zhu	zhu	PROPN
cana-6092	144	2	,	,	PUNCT
cana-6092	144	3	j.-y	j.-y	PROPN
cana-6092	144	4	.	.	PUNCT
cana-6092	144	5	,	,	PUNCT
cana-6092	144	6	park	park	NOUN
cana-6092	144	7	,	,	PUNCT
cana-6092	144	8	t.	t.	PROPN
cana-6092	144	9	,	,	PUNCT
cana-6092	144	10	isola	isola	PROPN
cana-6092	144	11	,	,	PUNCT
cana-6092	144	12	p.	p.	PROPN
cana-6092	144	13	,	,	PUNCT
cana-6092	144	14	&	&	CCONJ
cana-6092	144	15	efros	efros	PROPN
cana-6092	144	16	,	,	PUNCT
cana-6092	144	17	a.	a.	NOUN
cana-6092	144	18	a.	a.	PROPN
cana-6092	144	19	(	(	PUNCT
cana-6092	144	20	2017	2017	NUM
cana-6092	144	21	)	)	PUNCT
cana-6092	144	22	.	.	PUNCT
cana-6092	145	1	unpaired	unpaired	ADJ
cana-6092	145	2	image	image	NOUN
cana-6092	145	3	-	-	PUNCT
cana-6092	145	4	to	to	ADP
cana-6092	145	5	-	-	PUNCT
cana-6092	145	6	image	image	NOUN
cana-6092	145	7	translation	translation	NOUN
cana-6092	145	8	using	use	VERB
cana-6092	145	9	cycleconsistent	cycleconsistent	NOUN
cana-6092	145	10	adversarial	adversarial	ADJ
cana-6092	145	11	networks	network	NOUN
cana-6092	145	12	.	.	PUNCT
cana-6092	146	1	in	in	ADP
cana-6092	146	2	proceedings	proceeding	NOUN
cana-6092	146	3	of	of	ADP
cana-6092	146	4	the	the	DET
cana-6092	146	5	ieee	ieee	NOUN
cana-6092	146	6	international	international	PROPN
cana-6092	146	7	conference	conference	NOUN
cana-6092	146	8	on	on	ADP
cana-6092	146	9	computer	computer	NOUN
cana-6092	146	10	vision	vision	NOUN
cana-6092	146	11	(	(	PUNCT
cana-6092	146	12	pp	pp	ADJ
cana-6092	146	13	.	.	PUNCT
cana-6092	147	1	2223–2232	2223–2232	NUM
cana-6092	147	2	)	)	PUNCT
cana-6092	147	3	.	.	PUNCT
cana-6092	148	1	10	10	NUM
cana-6092	148	2	.	.	X
cana-6092	149	1	gulrajani	gulrajani	PROPN
cana-6092	149	2	,	,	PUNCT
cana-6092	149	3	i.	i.	PROPN
cana-6092	149	4	,	,	PUNCT
cana-6092	149	5	ahmed	ahmed	PROPN
cana-6092	149	6	,	,	PUNCT
cana-6092	149	7	f.	f.	PROPN
cana-6092	149	8	,	,	PUNCT
cana-6092	149	9	arjovsky	arjovsky	PROPN
cana-6092	149	10	,	,	PUNCT
cana-6092	149	11	m.	m.	NOUN
cana-6092	149	12	,	,	PUNCT
cana-6092	149	13	dumoulin	dumoulin	PROPN
cana-6092	149	14	,	,	PUNCT
cana-6092	149	15	v.	v.	ADV
cana-6092	149	16	,	,	PUNCT
cana-6092	149	17	&	&	CCONJ
cana-6092	149	18	courville	courville	PROPN
cana-6092	149	19	,	,	PUNCT
cana-6092	149	20	a.	a.	PROPN
cana-6092	149	21	c.	c.	PROPN
cana-6092	149	22	(	(	PUNCT
cana-6092	149	23	2017	2017	NUM
cana-6092	149	24	)	)	PUNCT
cana-6092	149	25	.	.	PUNCT
cana-6092	150	1	improved	improved	ADJ
cana-6092	150	2	training	training	NOUN
cana-6092	150	3	of	of	ADP
cana-6092	150	4	wasserstein	wasserstein	NOUN
cana-6092	150	5	gans	gans	PROPN
cana-6092	150	6	.	.	PUNCT
cana-6092	151	1	advances	advance	NOUN
cana-6092	151	2	in	in	ADP
cana-6092	151	3	neural	neural	ADJ
cana-6092	151	4	information	information	NOUN
cana-6092	151	5	processing	processing	NOUN
cana-6092	151	6	systems	system	NOUN
cana-6092	151	7	,	,	PUNCT
cana-6092	151	8	30	30	NUM
cana-6092	151	9	.	.	NOUN
cana-6092	151	10	11	11	NUM
cana-6092	151	11	.	.	X
cana-6092	152	1	bora	bora	PROPN
cana-6092	152	2	,	,	PUNCT
cana-6092	152	3	a.	a.	PROPN
cana-6092	152	4	,	,	PUNCT
cana-6092	152	5	jalal	jalal	PROPN
cana-6092	152	6	,	,	PUNCT
cana-6092	152	7	a.	a.	NOUN
cana-6092	152	8	,	,	PUNCT
cana-6092	152	9	price	price	NOUN
cana-6092	152	10	,	,	PUNCT
cana-6092	152	11	e.	e.	PROPN
cana-6092	152	12	,	,	PUNCT
cana-6092	152	13	&	&	CCONJ
cana-6092	152	14	dimakis	dimakis	PROPN
cana-6092	152	15	,	,	PUNCT
cana-6092	152	16	a.	a.	NOUN
cana-6092	152	17	g.	g.	PROPN
cana-6092	152	18	(	(	PUNCT
cana-6092	152	19	2017	2017	NUM
cana-6092	152	20	)	)	PUNCT
cana-6092	152	21	.	.	PUNCT
cana-6092	153	1	compressed	compress	VERB
cana-6092	153	2	sensing	sense	VERB
cana-6092	153	3	using	use	VERB
cana-6092	153	4	generative	generative	ADJ
cana-6092	153	5	models	model	NOUN
cana-6092	153	6	.	.	PUNCT
cana-6092	154	1	in	in	ADP
cana-6092	154	2	international	international	ADJ
cana-6092	154	3	conference	conference	NOUN
cana-6092	154	4	on	on	ADP
cana-6092	154	5	machine	machine	NOUN
cana-6092	154	6	learning	learning	NOUN
cana-6092	154	7	(	(	PUNCT
cana-6092	154	8	pp	pp	ADJ
cana-6092	154	9	.	.	PUNCT
cana-6092	155	1	537–546	537–546	NUM
cana-6092	155	2	)	)	PUNCT
cana-6092	155	3	.	.	PUNCT
cana-6092	156	1	pmlr	pmlr	NOUN
cana-6092	156	2	.	.	PUNCT
cana-6092	157	1	12	12	NUM
cana-6092	157	2	.	.	PUNCT
cana-6092	158	1	adler	adler	PROPN
cana-6092	158	2	,	,	PUNCT
cana-6092	158	3	j.	j.	PROPN
cana-6092	158	4	,	,	PUNCT
cana-6092	158	5	&	&	CCONJ
cana-6092	158	6	öktem	öktem	PROPN
cana-6092	158	7	,	,	PUNCT
cana-6092	158	8	o.	o.	PROPN
cana-6092	158	9	(	(	PUNCT
cana-6092	158	10	2017	2017	NUM
cana-6092	158	11	)	)	PUNCT
cana-6092	158	12	.	.	PUNCT
cana-6092	159	1	solving	solve	VERB
cana-6092	159	2	ill	ill	ADV
cana-6092	159	3	-	-	PUNCT
cana-6092	159	4	posed	pose	VERB
cana-6092	159	5	inverse	inverse	NOUN
cana-6092	159	6	problems	problem	NOUN
cana-6092	159	7	using	use	VERB
cana-6092	159	8	iterative	iterative	NOUN
cana-6092	159	9	deep	deep	ADJ
cana-6092	159	10	neural	neural	ADJ
cana-6092	159	11	networks	network	NOUN
cana-6092	159	12	.	.	PUNCT
cana-6092	160	1	inverse	inverse	NOUN
cana-6092	160	2	problems	problem	NOUN
cana-6092	160	3	,	,	PUNCT
cana-6092	160	4	33(12	33(12	NUM
cana-6092	160	5	)	)	PUNCT
cana-6092	160	6	,	,	PUNCT
cana-6092	160	7	124007	124007	NUM
cana-6092	160	8	.	.	PUNCT
cana-6092	161	1	13	13	NUM
cana-6092	161	2	.	.	PUNCT
cana-6092	161	3	lucas	lucas	PROPN
cana-6092	161	4	,	,	PUNCT
cana-6092	161	5	a.	a.	NOUN
cana-6092	161	6	,	,	PUNCT
cana-6092	161	7	iliadis	iliadis	PROPN
cana-6092	161	8	,	,	PUNCT
cana-6092	161	9	m.	m.	NOUN
cana-6092	161	10	,	,	PUNCT
cana-6092	161	11	molina	molina	PROPN
cana-6092	161	12	,	,	PUNCT
cana-6092	161	13	r.	r.	PROPN
cana-6092	161	14	,	,	PUNCT
cana-6092	161	15	&	&	CCONJ
cana-6092	161	16	katsaggelos	katsaggelos	PROPN
cana-6092	161	17	,	,	PUNCT
cana-6092	161	18	a.	a.	PROPN
cana-6092	161	19	k.	k.	PROPN
cana-6092	161	20	(	(	PUNCT
cana-6092	161	21	2018	2018	NUM
cana-6092	161	22	)	)	PUNCT
cana-6092	161	23	.	.	PUNCT
cana-6092	162	1	using	use	VERB
cana-6092	162	2	deep	deep	ADJ
cana-6092	162	3	neural	neural	ADJ
cana-6092	162	4	networks	network	NOUN
cana-6092	162	5	for	for	ADP
cana-6092	162	6	inverse	inverse	NOUN
cana-6092	162	7	problems	problem	NOUN
cana-6092	162	8	in	in	ADP
cana-6092	162	9	imaging	imaging	NOUN
cana-6092	162	10	:	:	PUNCT
cana-6092	162	11	beyond	beyond	ADP
cana-6092	162	12	analytical	analytical	ADJ
cana-6092	162	13	methods	method	NOUN
cana-6092	162	14	.	.	PUNCT
cana-6092	163	1	ieee	ieee	NOUN
cana-6092	163	2	signal	signal	PROPN
cana-6092	163	3	processing	processing	NOUN
cana-6092	163	4	magazine	magazine	NOUN
cana-6092	163	5	,	,	PUNCT
cana-6092	163	6	35(1	35(1	NUM
cana-6092	163	7	)	)	PUNCT
cana-6092	163	8	,	,	PUNCT
cana-6092	163	9	20–36	20–36	NUM
cana-6092	163	10	.	.	PUNCT
cana-6092	164	1	14	14	NUM
cana-6092	164	2	.	.	PUNCT
cana-6092	164	3	litjens	litjen	NOUN
cana-6092	164	4	,	,	PUNCT
cana-6092	164	5	g.	g.	PROPN
cana-6092	164	6	,	,	PUNCT
cana-6092	164	7	kooi	kooi	PROPN
cana-6092	164	8	,	,	PUNCT
cana-6092	164	9	t.	t.	PROPN
cana-6092	164	10	,	,	PUNCT
cana-6092	164	11	bejnordi	bejnordi	PROPN
cana-6092	164	12	,	,	PUNCT
cana-6092	164	13	b.	b.	PROPN
cana-6092	164	14	e.	e.	PROPN
cana-6092	164	15	,	,	PUNCT
cana-6092	164	16	setio	setio	PROPN
cana-6092	164	17	,	,	PUNCT
cana-6092	164	18	a.	a.	PROPN
cana-6092	164	19	a.	a.	NOUN
cana-6092	164	20	a.	a.	PROPN
cana-6092	164	21	,	,	PUNCT
cana-6092	164	22	ciompi	ciompi	PROPN
cana-6092	164	23	,	,	PUNCT
cana-6092	164	24	f.	f.	PROPN
cana-6092	164	25	,	,	PUNCT
cana-6092	164	26	ghafoorian	ghafoorian	PROPN
cana-6092	164	27	,	,	PUNCT
cana-6092	164	28	m.	m.	NOUN
cana-6092	164	29	,	,	PUNCT
cana-6092	164	30	...	...	PUNCT
cana-6092	164	31	&	&	CCONJ
cana-6092	164	32	sánchez	sánchez	PROPN
cana-6092	164	33	,	,	PUNCT
cana-6092	164	34	c.	c.	PROPN
cana-6092	164	35	i.	i.	PROPN
cana-6092	164	36	(	(	PUNCT
cana-6092	164	37	2017	2017	NUM
cana-6092	164	38	)	)	PUNCT
cana-6092	164	39	.	.	PUNCT
cana-6092	165	1	a	a	DET
cana-6092	165	2	survey	survey	NOUN
cana-6092	165	3	on	on	ADP
cana-6092	165	4	deep	deep	ADJ
cana-6092	165	5	learning	learning	NOUN
cana-6092	165	6	in	in	ADP
cana-6092	165	7	medical	medical	ADJ
cana-6092	165	8	image	image	NOUN
cana-6092	165	9	analysis	analysis	NOUN
cana-6092	165	10	.	.	PUNCT
cana-6092	166	1	medical	medical	ADJ
cana-6092	166	2	image	image	NOUN
cana-6092	166	3	analysis	analysis	NOUN
cana-6092	166	4	,	,	PUNCT
cana-6092	166	5	42	42	NUM
cana-6092	166	6	,	,	PUNCT
cana-6092	166	7	60–88	60–88	NUM
cana-6092	166	8	.	.	PUNCT
cana-6092	167	1	15	15	NUM
cana-6092	167	2	.	.	PUNCT
cana-6092	167	3	antun	antun	PROPN
cana-6092	167	4	,	,	PUNCT
cana-6092	167	5	v.	v.	PROPN
cana-6092	167	6	,	,	PUNCT
cana-6092	167	7	renna	renna	PROPN
cana-6092	167	8	,	,	PUNCT
cana-6092	167	9	f.	f.	PROPN
cana-6092	167	10	,	,	PUNCT
cana-6092	167	11	poon	poon	NOUN
cana-6092	167	12	,	,	PUNCT
cana-6092	167	13	c.	c.	NOUN
cana-6092	167	14	,	,	PUNCT
cana-6092	167	15	adcock	adcock	NOUN
cana-6092	167	16	,	,	PUNCT
cana-6092	167	17	b.	b.	PROPN
cana-6092	167	18	,	,	PUNCT
cana-6092	167	19	&	&	CCONJ
cana-6092	167	20	hansen	hansen	PROPN
cana-6092	167	21	,	,	PUNCT
cana-6092	167	22	a.	a.	PROPN
cana-6092	167	23	c.	c.	PROPN
cana-6092	167	24	(	(	PUNCT
cana-6092	167	25	2020	2020	NUM
cana-6092	167	26	)	)	PUNCT
cana-6092	167	27	.	.	PUNCT
cana-6092	168	1	on	on	ADP
cana-6092	168	2	instabilities	instability	NOUN
cana-6092	168	3	of	of	ADP
cana-6092	168	4	deep	deep	ADJ
cana-6092	168	5	learning	learning	NOUN
cana-6092	168	6	in	in	ADP
cana-6092	168	7	image	image	NOUN
cana-6092	168	8	reconstruction	reconstruction	NOUN
cana-6092	168	9	and	and	CCONJ
cana-6092	168	10	the	the	DET
cana-6092	168	11	potential	potential	ADJ
cana-6092	168	12	costs	cost	NOUN
cana-6092	168	13	of	of	ADP
cana-6092	168	14	ai	ai	NOUN
cana-6092	168	15	.	.	PUNCT
cana-6092	169	1	proceedings	proceeding	NOUN
cana-6092	169	2	of	of	ADP
cana-6092	169	3	the	the	DET
cana-6092	169	4	national	national	PROPN
cana-6092	169	5	academy	academy	PROPN
cana-6092	169	6	of	of	ADP
cana-6092	169	7	sciences	sciences	PROPN
cana-6092	169	8	,	,	PUNCT
cana-6092	169	9	117(48	117(48	NUM
cana-6092	169	10	)	)	PUNCT
cana-6092	169	11	,	,	PUNCT
cana-6092	169	12	30088–30095	30088–30095	NUM
cana-6092	169	13	.	.	PUNCT
cana-6092	169	14	16	16	NUM
cana-6092	169	15	.	.	PUNCT
cana-6092	170	1	evangelista	evangelista	PROPN
cana-6092	170	2	,	,	PUNCT
cana-6092	170	3	d.	d.	PROPN
cana-6092	170	4	,	,	PUNCT
cana-6092	170	5	kelly	kelly	PROPN
cana-6092	170	6	,	,	PUNCT
cana-6092	170	7	b.	b.	PROPN
cana-6092	170	8	,	,	PUNCT
cana-6092	170	9	&	&	CCONJ
cana-6092	170	10	datta	datta	PROPN
cana-6092	170	11	,	,	PUNCT
cana-6092	170	12	a.	a.	NOUN
cana-6092	170	13	(	(	PUNCT
cana-6092	170	14	2023	2023	NUM
cana-6092	170	15	)	)	PUNCT
cana-6092	170	16	.	.	PUNCT
cana-6092	171	1	the	the	DET
cana-6092	171	2	stability	stability	NOUN
cana-6092	171	3	-	-	PUNCT
cana-6092	171	4	accuracy	accuracy	NOUN
cana-6092	171	5	trade	trade	NOUN
cana-6092	171	6	-	-	PUNCT
cana-6092	171	7	off	off	NOUN
cana-6092	171	8	in	in	ADP
cana-6092	171	9	neural	neural	ADJ
cana-6092	171	10	networks	network	NOUN
cana-6092	171	11	for	for	ADP
cana-6092	171	12	inverse	inverse	NOUN
cana-6092	171	13	problems	problem	NOUN
cana-6092	171	14	.	.	PUNCT
cana-6092	172	1	journal	journal	NOUN
cana-6092	172	2	of	of	ADP
cana-6092	172	3	machine	machine	NOUN
cana-6092	172	4	learning	learn	VERB
cana-6092	172	5	research	research	NOUN
cana-6092	172	6	,	,	PUNCT
cana-6092	172	7	24(123	24(123	NOUN
cana-6092	172	8	)	)	PUNCT
cana-6092	172	9	,	,	PUNCT
cana-6092	172	10	1	1	NUM
cana-6092	172	11	-	-	SYM
cana-6092	172	12	42	42	NUM
cana-6092	172	13	.	.	PUNCT
cana-6092	173	1	17	17	NUM
cana-6092	173	2	.	.	PUNCT
cana-6092	173	3	venkatakrishnan	venkatakrishnan	NOUN
cana-6092	173	4	,	,	PUNCT
cana-6092	173	5	s.	s.	PROPN
cana-6092	173	6	v.	v.	PROPN
cana-6092	173	7	,	,	PUNCT
cana-6092	173	8	bouman	bouman	ADJ
cana-6092	173	9	,	,	PUNCT
cana-6092	173	10	c.	c.	PROPN
cana-6092	173	11	a.	a.	PROPN
cana-6092	173	12	,	,	PUNCT
cana-6092	173	13	&	&	CCONJ
cana-6092	173	14	wohlberg	wohlberg	PROPN
cana-6092	173	15	,	,	PUNCT
cana-6092	173	16	b.	b.	PROPN
cana-6092	173	17	(	(	PUNCT
cana-6092	173	18	2013	2013	NUM
cana-6092	173	19	)	)	PUNCT
cana-6092	173	20	.	.	PUNCT
cana-6092	174	1	plug	plug	VERB
cana-6092	174	2	-	-	PUNCT
cana-6092	174	3	and	and	CCONJ
cana-6092	174	4	-	-	PUNCT
cana-6092	174	5	play	play	NOUN
cana-6092	174	6	priors	prior	NOUN
cana-6092	174	7	for	for	ADP
cana-6092	174	8	model	model	NOUN
cana-6092	174	9	based	base	VERB
cana-6092	174	10	reconstruction	reconstruction	NOUN
cana-6092	174	11	.	.	PUNCT
cana-6092	175	1	in	in	ADP
cana-6092	175	2	2013	2013	NUM
cana-6092	175	3	ieee	ieee	NOUN
cana-6092	175	4	global	global	ADJ
cana-6092	175	5	conference	conference	NOUN
cana-6092	175	6	on	on	ADP
cana-6092	175	7	signal	signal	NOUN
cana-6092	175	8	and	and	CCONJ
cana-6092	175	9	information	information	NOUN
cana-6092	175	10	processing	processing	NOUN
cana-6092	175	11	(	(	PUNCT
cana-6092	175	12	pp	pp	ADJ
cana-6092	175	13	.	.	PUNCT
cana-6092	176	1	945–948	945–948	NUM
cana-6092	176	2	)	)	PUNCT
cana-6092	176	3	.	.	PUNCT
cana-6092	177	1	ieee	ieee	PROPN
cana-6092	177	2	.	.	PUNCT
cana-6092	178	1	18	18	NUM
cana-6092	178	2	.	.	X
cana-6092	179	1	wang	wang	PROPN
cana-6092	179	2	,	,	PUNCT
cana-6092	179	3	s.	s.	PROPN
cana-6092	179	4	,	,	PUNCT
cana-6092	179	5	su	su	PROPN
cana-6092	179	6	,	,	PUNCT
cana-6092	179	7	z.	z.	PROPN
cana-6092	179	8	,	,	PUNCT
cana-6092	179	9	ying	ying	PROPN
cana-6092	179	10	,	,	PUNCT
cana-6092	179	11	l.	l.	PROPN
cana-6092	179	12	,	,	PUNCT
cana-6092	179	13	peng	peng	PROPN
cana-6092	179	14	,	,	PUNCT
cana-6092	179	15	x.	x.	PROPN
cana-6092	179	16	,	,	PUNCT
cana-6092	179	17	zhu	zhu	PROPN
cana-6092	179	18	,	,	PUNCT
cana-6092	179	19	s.	s.	PROPN
cana-6092	179	20	,	,	PUNCT
cana-6092	179	21	liang	liang	PROPN
cana-6092	179	22	,	,	PUNCT
cana-6092	179	23	f.	f.	PROPN
cana-6092	179	24	,	,	PUNCT
cana-6092	179	25	...	...	PUNCT
cana-6092	179	26	&	&	CCONJ
cana-6092	179	27	liang	liang	PROPN
cana-6092	179	28	,	,	PUNCT
cana-6092	179	29	d.	d.	PROPN
cana-6092	179	30	(	(	PUNCT
cana-6092	179	31	2016	2016	NUM
cana-6092	179	32	)	)	PUNCT
cana-6092	179	33	.	.	PUNCT
cana-6092	180	1	accelerating	accelerate	VERB
cana-6092	180	2	magnetic	magnetic	ADJ
cana-6092	180	3	resonance	resonance	NOUN
cana-6092	180	4	imaging	imaging	NOUN
cana-6092	180	5	via	via	ADP
cana-6092	180	6	deep	deep	ADJ
cana-6092	180	7	learning	learning	NOUN
cana-6092	180	8	.	.	PUNCT
cana-6092	181	1	in	in	ADP
cana-6092	181	2	2016	2016	NUM
cana-6092	181	3	ieee	ieee	NOUN
cana-6092	181	4	13th	13th	NOUN
cana-6092	181	5	international	international	ADJ
cana-6092	181	6	symposium	symposium	NOUN
cana-6092	181	7	on	on	ADP
cana-6092	181	8	biomedical	biomedical	ADJ
cana-6092	181	9	imaging	imaging	NOUN
cana-6092	181	10	(	(	PUNCT
cana-6092	181	11	isbi	isbi	NOUN
cana-6092	181	12	)	)	PUNCT
cana-6092	181	13	(	(	PUNCT
cana-6092	181	14	pp	pp	ADV
cana-6092	181	15	.	.	PUNCT
cana-6092	182	1	514–517	514–517	NUM
cana-6092	182	2	)	)	PUNCT
cana-6092	182	3	.	.	PUNCT
cana-6092	183	1	ieee	ieee	PROPN
cana-6092	183	2	.	.	PUNCT
cana-6092	184	1	19	19	NUM
cana-6092	184	2	.	.	X
cana-6092	184	3	yang	yang	PROPN
cana-6092	184	4	,	,	PUNCT
cana-6092	184	5	y.	y.	PROPN
cana-6092	184	6	,	,	PUNCT
cana-6092	184	7	sun	sun	PROPN
cana-6092	184	8	,	,	PUNCT
cana-6092	184	9	j.	j.	PROPN
cana-6092	184	10	,	,	PUNCT
cana-6092	184	11	li	li	PROPN
cana-6092	184	12	,	,	PUNCT
cana-6092	184	13	h.	h.	PROPN
cana-6092	184	14	,	,	PUNCT
cana-6092	184	15	&	&	CCONJ
cana-6092	184	16	xu	xu	PROPN
cana-6092	184	17	,	,	PUNCT
cana-6092	184	18	z.	z.	PROPN
cana-6092	184	19	(	(	PUNCT
cana-6092	184	20	2018	2018	NUM
cana-6092	184	21	)	)	PUNCT
cana-6092	184	22	.	.	PUNCT
cana-6092	185	1	admm	admm	NOUN
cana-6092	185	2	-	-	PUNCT
cana-6092	185	3	csnet	csnet	NOUN
cana-6092	185	4	:	:	PUNCT
cana-6092	185	5	a	a	DET
cana-6092	185	6	deep	deep	ADJ
cana-6092	185	7	learning	learning	NOUN
cana-6092	185	8	approach	approach	NOUN
cana-6092	185	9	for	for	ADP
cana-6092	185	10	image	image	NOUN
cana-6092	185	11	compressive	compressive	ADJ
cana-6092	185	12	sensing	sensing	NOUN
cana-6092	185	13	.	.	PUNCT
cana-6092	186	1	ieee	ieee	NOUN
cana-6092	186	2	transactions	transaction	NOUN
cana-6092	186	3	on	on	ADP
cana-6092	186	4	pattern	pattern	NOUN
cana-6092	186	5	analysis	analysis	NOUN
cana-6092	186	6	and	and	CCONJ
cana-6092	186	7	machine	machine	NOUN
cana-6092	186	8	intelligence	intelligence	NOUN
cana-6092	186	9	,	,	PUNCT
cana-6092	186	10	42(3	42(3	NUM
cana-6092	186	11	)	)	PUNCT
cana-6092	186	12	,	,	PUNCT
cana-6092	186	13	521–538	521–538	NUM
cana-6092	186	14	.	.	PUNCT
cana-6092	187	1	20	20	NUM
cana-6092	187	2	.	.	X
cana-6092	188	1	richardson	richardson	PROPN
cana-6092	188	2	,	,	PUNCT
cana-6092	188	3	c.	c.	PROPN
cana-6092	188	4	l.	l.	PROPN
cana-6092	188	5	,	,	PUNCT
cana-6092	188	6	&	&	CCONJ
cana-6092	188	7	olson	olson	PROPN
cana-6092	188	8	,	,	PUNCT
cana-6092	188	9	l.	l.	PROPN
cana-6092	188	10	r.	r.	PROPN
cana-6092	188	11	(	(	PUNCT
cana-6092	188	12	2021	2021	NUM
cana-6092	188	13	)	)	PUNCT
cana-6092	188	14	.	.	PUNCT
cana-6092	189	1	learning	learn	VERB
cana-6092	189	2	to	to	PART
cana-6092	189	3	solve	solve	VERB
cana-6092	189	4	inverse	inverse	NOUN
cana-6092	189	5	problems	problem	NOUN
cana-6092	189	6	in	in	ADP
cana-6092	189	7	imaging	imaging	NOUN
cana-6092	189	8	with	with	ADP
cana-6092	189	9	data	data	NOUN
cana-6092	189	10	-	-	PUNCT
cana-6092	189	11	driven	drive	VERB
cana-6092	189	12	priors	prior	NOUN
cana-6092	189	13	:	:	PUNCT
cana-6092	189	14	a	a	DET
cana-6092	189	15	review	review	NOUN
cana-6092	189	16	.	.	PUNCT
cana-6092	190	1	ieee	ieee	NOUN
cana-6092	190	2	transactions	transaction	NOUN
cana-6092	190	3	on	on	ADP
cana-6092	190	4	computational	computational	ADJ
cana-6092	190	5	imaging	imaging	NOUN
cana-6092	190	6	,	,	PUNCT
cana-6092	190	7	7	7	NUM
cana-6092	190	8	,	,	PUNCT
cana-6092	190	9	693–710	693–710	NUM
cana-6092	190	10	.	.	PUNCT
cana-6092	191	1	21	21	NUM
cana-6092	191	2	.	.	PUNCT
cana-6092	191	3	ongie	ongie	PROPN
cana-6092	191	4	,	,	PUNCT
cana-6092	191	5	g.	g.	PROPN
cana-6092	191	6	,	,	PUNCT
cana-6092	191	7	jalal	jalal	PROPN
cana-6092	191	8	,	,	PUNCT
cana-6092	191	9	a.	a.	PROPN
cana-6092	191	10	,	,	PUNCT
cana-6092	191	11	metzler	metzler	NOUN
cana-6092	191	12	,	,	PUNCT
cana-6092	191	13	c.	c.	PROPN
cana-6092	191	14	a.	a.	PROPN
cana-6092	191	15	,	,	PUNCT
cana-6092	191	16	baraniuk	baraniuk	PROPN
cana-6092	191	17	,	,	PUNCT
cana-6092	191	18	r.	r.	PROPN
cana-6092	191	19	g.	g.	PROPN
cana-6092	191	20	,	,	PUNCT
cana-6092	191	21	dimakis	dimakis	PROPN
cana-6092	191	22	,	,	PUNCT
cana-6092	191	23	a.	a.	NOUN
cana-6092	191	24	g.	g.	PROPN
cana-6092	191	25	,	,	PUNCT
cana-6092	191	26	&	&	CCONJ
cana-6092	191	27	willett	willett	PROPN
cana-6092	191	28	,	,	PUNCT
cana-6092	191	29	r.	r.	PROPN
cana-6092	191	30	(	(	PUNCT
cana-6092	191	31	2020	2020	NUM
cana-6092	191	32	)	)	PUNCT
cana-6092	191	33	.	.	PUNCT
cana-6092	192	1	deep	deep	ADJ
cana-6092	192	2	learning	learning	NOUN
cana-6092	192	3	techniques	technique	NOUN
cana-6092	192	4	for	for	ADP
cana-6092	192	5	inverse	inverse	NOUN
cana-6092	192	6	problems	problem	NOUN
cana-6092	192	7	in	in	ADP
cana-6092	192	8	imaging	imaging	NOUN
cana-6092	192	9	.	.	PUNCT
cana-6092	193	1	ieee	ieee	PROPN
cana-6092	193	2	journal	journal	PROPN
cana-6092	193	3	on	on	ADP
cana-6092	193	4	selected	select	VERB
cana-6092	193	5	areas	area	NOUN
cana-6092	193	6	in	in	ADP
cana-6092	193	7	information	information	NOUN
cana-6092	193	8	theory	theory	NOUN
cana-6092	193	9	,	,	PUNCT
cana-6092	193	10	1(1	1(1	NUM
cana-6092	193	11	)	)	PUNCT
cana-6092	193	12	,	,	PUNCT
cana-6092	193	13	39	39	NUM
cana-6092	193	14	–	–	PUNCT
cana-6092	193	15	56	56	NUM
cana-6092	193	16	.	.	PUNCT
cana-6092	194	1	communications	communication	NOUN
cana-6092	194	2	on	on	ADP
cana-6092	194	3	applied	apply	VERB
cana-6092	194	4	nonlinear	nonlinear	ADJ
cana-6092	194	5	analysis	analysis	NOUN
cana-6092	194	6	issn	issn	NOUN
cana-6092	194	7	:	:	PUNCT
cana-6092	194	8	1074	1074	NUM
cana-6092	194	9	-	-	PUNCT
cana-6092	194	10	133x	133x	NUM
cana-6092	194	11	vol	vol	NOUN
cana-6092	194	12	31	31	NUM
cana-6092	194	13	no	no	NOUN
cana-6092	194	14	.	.	NOUN
cana-6092	194	15	2	2	NUM
cana-6092	194	16	(	(	PUNCT
cana-6092	194	17	2024	2024	NUM
cana-6092	194	18	)	)	PUNCT
cana-6092	194	19	508	508	NUM
cana-6092	194	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	194	21	22	22	NUM
cana-6092	194	22	.	.	PUNCT
cana-6092	195	1	wu	wu	PROPN
cana-6092	195	2	,	,	PUNCT
cana-6092	195	3	y.	y.	PROPN
cana-6092	195	4	,	,	PUNCT
cana-6092	195	5	&	&	CCONJ
cana-6092	195	6	lin	lin	PROPN
cana-6092	195	7	,	,	PUNCT
cana-6092	195	8	y.	y.	PROPN
cana-6092	195	9	(	(	PUNCT
cana-6092	195	10	2019	2019	NUM
cana-6092	195	11	)	)	PUNCT
cana-6092	195	12	.	.	PUNCT
cana-6092	196	1	inverse	inverse	PROPN
cana-6092	196	2	generative	generative	ADJ
cana-6092	196	3	adversarial	adversarial	ADJ
cana-6092	196	4	networks	network	NOUN
cana-6092	196	5	.	.	PUNCT
cana-6092	197	1	in	in	ADP
cana-6092	197	2	proceedings	proceeding	NOUN
cana-6092	197	3	of	of	ADP
cana-6092	197	4	the	the	DET
cana-6092	197	5	ieee	ieee	NOUN
cana-6092	197	6	/	/	SYM
cana-6092	197	7	cvf	cvf	NOUN
cana-6092	197	8	conference	conference	NOUN
cana-6092	197	9	on	on	ADP
cana-6092	197	10	computer	computer	NOUN
cana-6092	197	11	vision	vision	NOUN
cana-6092	197	12	and	and	CCONJ
cana-6092	197	13	pattern	pattern	NOUN
cana-6092	197	14	recognition	recognition	NOUN
cana-6092	197	15	(	(	PUNCT
cana-6092	197	16	pp	pp	ADJ
cana-6092	197	17	.	.	PUNCT
cana-6092	198	1	5634–5643	5634–5643	NUM
cana-6092	198	2	)	)	PUNCT
cana-6092	198	3	.	.	PUNCT
cana-6092	199	1	23	23	NUM
cana-6092	199	2	.	.	PUNCT
cana-6092	200	1	li	li	PROPN
cana-6092	200	2	,	,	PUNCT
cana-6092	200	3	z.	z.	PROPN
cana-6092	200	4	,	,	PUNCT
cana-6092	200	5	zheng	zheng	PROPN
cana-6092	200	6	,	,	PUNCT
cana-6092	200	7	c.	c.	PROPN
cana-6092	200	8	,	,	PUNCT
cana-6092	200	9	&	&	CCONJ
cana-6092	200	10	liu	liu	PROPN
cana-6092	200	11	,	,	PUNCT
cana-6092	200	12	q.	q.	PROPN
cana-6092	200	13	(	(	PUNCT
cana-6092	200	14	2022	2022	NUM
cana-6092	200	15	)	)	PUNCT
cana-6092	200	16	.	.	PUNCT
cana-6092	201	1	differentiable	differentiable	ADJ
cana-6092	201	2	simulation	simulation	NOUN
cana-6092	201	3	for	for	ADP
cana-6092	201	4	robust	robust	ADJ
cana-6092	201	5	and	and	CCONJ
cana-6092	201	6	scalable	scalable	ADJ
cana-6092	201	7	inverse	inverse	NOUN
cana-6092	201	8	problems	problem	NOUN
cana-6092	201	9	.	.	PUNCT
cana-6092	202	1	advances	advance	NOUN
cana-6092	202	2	in	in	ADP
cana-6092	202	3	neural	neural	ADJ
cana-6092	202	4	information	information	NOUN
cana-6092	202	5	processing	processing	NOUN
cana-6092	202	6	systems	system	NOUN
cana-6092	202	7	,	,	PUNCT
cana-6092	202	8	35	35	NUM
cana-6092	202	9	.	.	NOUN
cana-6092	202	10	24	24	NUM
cana-6092	202	11	.	.	PUNCT
cana-6092	203	1	araya	araya	PROPN
cana-6092	203	2	-	-	PUNCT
cana-6092	203	3	polo	polo	PROPN
cana-6092	203	4	,	,	PUNCT
cana-6092	203	5	m.	m.	NOUN
cana-6092	203	6	,	,	PUNCT
cana-6092	203	7	jennings	jennings	PROPN
cana-6092	203	8	,	,	PUNCT
cana-6092	203	9	j.	j.	PROPN
cana-6092	203	10	,	,	PUNCT
cana-6092	203	11	adler	adler	PROPN
cana-6092	203	12	,	,	PUNCT
cana-6092	203	13	a.	a.	PROPN
cana-6092	203	14	,	,	PUNCT
cana-6092	203	15	&	&	CCONJ
cana-6092	203	16	dahlke	dahlke	PROPN
cana-6092	203	17	,	,	PUNCT
cana-6092	203	18	t.	t.	PROPN
cana-6092	203	19	(	(	PUNCT
cana-6092	203	20	2018	2018	NUM
cana-6092	203	21	)	)	PUNCT
cana-6092	203	22	.	.	PUNCT
cana-6092	204	1	deep	deep	ADJ
cana-6092	204	2	-	-	PUNCT
cana-6092	204	3	learning	learn	VERB
cana-6092	204	4	tomography	tomography	NOUN
cana-6092	204	5	.	.	PUNCT
cana-6092	205	1	the	the	DET
cana-6092	205	2	leading	lead	VERB
cana-6092	205	3	edge	edge	NOUN
cana-6092	205	4	,	,	PUNCT
cana-6092	205	5	37(1	37(1	NUM
cana-6092	205	6	)	)	PUNCT
cana-6092	205	7	,	,	PUNCT
cana-6092	205	8	58–66	58–66	NUM
cana-6092	205	9	.	.	PUNCT
cana-6092	206	1	25	25	NUM
cana-6092	206	2	.	.	X
cana-6092	207	1	yang	yang	PROPN
cana-6092	207	2	,	,	PUNCT
cana-6092	207	3	f.	f.	PROPN
cana-6092	207	4	,	,	PUNCT
cana-6092	207	5	&	&	CCONJ
cana-6092	207	6	ma	ma	PROPN
cana-6092	207	7	,	,	PUNCT
cana-6092	207	8	j.	j.	PROPN
cana-6092	207	9	(	(	PUNCT
cana-6092	207	10	2019	2019	NUM
cana-6092	207	11	)	)	PUNCT
cana-6092	207	12	.	.	PUNCT
cana-6092	208	1	deep	deep	ADJ
cana-6092	208	2	-	-	PUNCT
cana-6092	208	3	learning	learn	VERB
cana-6092	208	4	inversion	inversion	NOUN
cana-6092	208	5	:	:	PUNCT
cana-6092	208	6	a	a	DET
cana-6092	208	7	next	next	ADJ
cana-6092	208	8	-	-	PUNCT
cana-6092	208	9	generation	generation	NOUN
cana-6092	208	10	seismic	seismic	ADJ
cana-6092	208	11	velocity	velocity	NOUN
cana-6092	208	12	model	model	NOUN
cana-6092	208	13	building	building	NOUN
cana-6092	208	14	method	method	NOUN
cana-6092	208	15	.	.	PUNCT
cana-6092	209	1	geophysics	geophysic	NOUN
cana-6092	209	2	,	,	PUNCT
cana-6092	209	3	84(4	84(4	NUM
cana-6092	209	4	)	)	PUNCT
cana-6092	209	5	,	,	PUNCT
cana-6092	209	6	r583	r583	PROPN
cana-6092	209	7	–	–	PUNCT
cana-6092	209	8	r599	r599	PROPN
cana-6092	209	9	.	.	PROPN
cana-6092	210	1	26	26	NUM
cana-6092	210	2	.	.	PUNCT
cana-6092	211	1	mosser	mosser	PROPN
cana-6092	211	2	,	,	PUNCT
cana-6092	211	3	l.	l.	PROPN
cana-6092	211	4	,	,	PUNCT
cana-6092	211	5	dubrule	dubrule	NOUN
cana-6092	211	6	,	,	PUNCT
cana-6092	211	7	o.	o.	NOUN
cana-6092	211	8	,	,	PUNCT
cana-6092	211	9	&	&	CCONJ
cana-6092	211	10	blunt	blunt	ADJ
cana-6092	211	11	,	,	PUNCT
cana-6092	211	12	m.	m.	NOUN
cana-6092	211	13	j.	j.	PROPN
cana-6092	211	14	(	(	PUNCT
cana-6092	211	15	2020	2020	NUM
cana-6092	211	16	)	)	PUNCT
cana-6092	211	17	.	.	PUNCT
cana-6092	212	1	stochastic	stochastic	ADJ
cana-6092	212	2	seismic	seismic	ADJ
cana-6092	212	3	waveform	waveform	NOUN
cana-6092	212	4	inversion	inversion	NOUN
cana-6092	212	5	using	use	VERB
cana-6092	212	6	generative	generative	ADJ
cana-6092	212	7	adversarial	adversarial	ADJ
cana-6092	212	8	networks	network	NOUN
cana-6092	212	9	as	as	ADP
cana-6092	212	10	a	a	DET
cana-6092	212	11	geological	geological	ADJ
cana-6092	212	12	prior	prior	NOUN
cana-6092	212	13	.	.	PUNCT
cana-6092	213	1	mathematical	mathematical	ADJ
cana-6092	213	2	geosciences	geoscience	NOUN
cana-6092	213	3	,	,	PUNCT
cana-6092	213	4	52(1	52(1	NOUN
cana-6092	213	5	)	)	PUNCT
cana-6092	213	6	,	,	PUNCT
cana-6092	213	7	53–79	53–79	NUM
cana-6092	213	8	.	.	PUNCT
cana-6092	214	1	27	27	NUM
cana-6092	214	2	.	.	PUNCT
cana-6092	215	1	kharazmi	kharazmi	PROPN
cana-6092	215	2	,	,	PUNCT
cana-6092	215	3	e.	e.	PROPN
cana-6092	215	4	,	,	PUNCT
cana-6092	215	5	zhang	zhang	PROPN
cana-6092	215	6	,	,	PUNCT
cana-6092	215	7	z.	z.	PROPN
cana-6092	215	8	,	,	PUNCT
cana-6092	215	9	&	&	CCONJ
cana-6092	215	10	karniadakis	karniadakis	PROPN
cana-6092	215	11	,	,	PUNCT
cana-6092	215	12	g.	g.	PROPN
cana-6092	215	13	e.	e.	PROPN
cana-6092	215	14	(	(	PUNCT
cana-6092	215	15	2021	2021	NUM
cana-6092	215	16	)	)	PUNCT
cana-6092	215	17	.	.	PUNCT
cana-6092	216	1	variational	variational	ADJ
cana-6092	216	2	physics	physics	NOUN
cana-6092	216	3	-	-	PUNCT
cana-6092	216	4	informed	inform	VERB
cana-6092	216	5	neural	neural	ADJ
cana-6092	216	6	networks	network	NOUN
cana-6092	216	7	for	for	ADP
cana-6092	216	8	solving	solve	VERB
cana-6092	216	9	partial	partial	ADJ
cana-6092	216	10	differential	differential	ADJ
cana-6092	216	11	equations	equation	NOUN
cana-6092	216	12	.	.	PUNCT
cana-6092	217	1	journal	journal	NOUN
cana-6092	217	2	of	of	ADP
cana-6092	217	3	computational	computational	ADJ
cana-6092	217	4	physics	physics	NOUN
cana-6092	217	5	,	,	PUNCT
cana-6092	217	6	446	446	NUM
cana-6092	217	7	,	,	PUNCT
cana-6092	217	8	110667	110667	NUM
cana-6092	217	9	.	.	PUNCT
cana-6092	218	1	28	28	NUM
cana-6092	218	2	.	.	X
cana-6092	219	1	lu	lu	PROPN
cana-6092	219	2	,	,	PUNCT
cana-6092	219	3	l.	l.	PROPN
cana-6092	219	4	,	,	PUNCT
cana-6092	219	5	meng	meng	PROPN
cana-6092	219	6	,	,	PUNCT
cana-6092	219	7	x.	x.	PROPN
cana-6092	219	8	,	,	PUNCT
cana-6092	219	9	mao	mao	PROPN
cana-6092	219	10	,	,	PUNCT
cana-6092	219	11	z.	z.	PROPN
cana-6092	219	12	,	,	PUNCT
cana-6092	219	13	&	&	CCONJ
cana-6092	219	14	karniadakis	karniadakis	PROPN
cana-6092	219	15	,	,	PUNCT
cana-6092	219	16	g.	g.	PROPN
cana-6092	219	17	e.	e.	PROPN
cana-6092	219	18	(	(	PUNCT
cana-6092	219	19	2021	2021	NUM
cana-6092	219	20	)	)	PUNCT
cana-6092	219	21	.	.	PUNCT
cana-6092	220	1	deepxde	deepxde	NOUN
cana-6092	220	2	:	:	PUNCT
cana-6092	220	3	a	a	DET
cana-6092	220	4	deep	deep	ADJ
cana-6092	220	5	learning	learning	NOUN
cana-6092	220	6	library	library	NOUN
cana-6092	220	7	for	for	ADP
cana-6092	220	8	solving	solve	VERB
cana-6092	220	9	differential	differential	ADJ
cana-6092	220	10	equations	equation	NOUN
cana-6092	220	11	.	.	PUNCT
cana-6092	221	1	siam	siam	PROPN
cana-6092	221	2	review	review	PROPN
cana-6092	221	3	,	,	PUNCT
cana-6092	221	4	63(1	63(1	NUM
cana-6092	221	5	)	)	PUNCT
cana-6092	221	6	,	,	PUNCT
cana-6092	221	7	208–228	208–228	NUM
cana-6092	221	8	.	.	NOUN
cana-6092	221	9	29	29	NUM
cana-6092	221	10	.	.	X
cana-6092	222	1	baydin	baydin	VERB
cana-6092	222	2	,	,	PUNCT
cana-6092	222	3	a.	a.	NOUN
cana-6092	222	4	g.	g.	PROPN
cana-6092	222	5	,	,	PUNCT
cana-6092	222	6	pearlmutter	pearlmutter	PROPN
cana-6092	222	7	,	,	PUNCT
cana-6092	222	8	b.	b.	PROPN
cana-6092	222	9	a.	a.	PROPN
cana-6092	222	10	,	,	PUNCT
cana-6092	222	11	radul	radul	VERB
cana-6092	222	12	,	,	PUNCT
cana-6092	222	13	a.	a.	NOUN
cana-6092	222	14	a.	a.	PROPN
cana-6092	222	15	,	,	PUNCT
cana-6092	222	16	&	&	CCONJ
cana-6092	222	17	siskind	siskind	PROPN
cana-6092	222	18	,	,	PUNCT
cana-6092	222	19	j.	j.	PROPN
cana-6092	222	20	m.	m.	PROPN
cana-6092	222	21	(	(	PUNCT
cana-6092	222	22	2018	2018	NUM
cana-6092	222	23	)	)	PUNCT
cana-6092	222	24	.	.	PUNCT
cana-6092	223	1	automatic	automatic	ADJ
cana-6092	223	2	differentiation	differentiation	NOUN
cana-6092	223	3	in	in	ADP
cana-6092	223	4	machine	machine	NOUN
cana-6092	223	5	learning	learning	NOUN
cana-6092	223	6	:	:	PUNCT
cana-6092	223	7	a	a	DET
cana-6092	223	8	survey	survey	NOUN
cana-6092	223	9	.	.	PUNCT
cana-6092	224	1	journal	journal	NOUN
cana-6092	224	2	of	of	ADP
cana-6092	224	3	machine	machine	NOUN
cana-6092	224	4	learning	learn	VERB
cana-6092	224	5	research	research	NOUN
cana-6092	224	6	,	,	PUNCT
cana-6092	224	7	18(1	18(1	NUM
cana-6092	224	8	)	)	PUNCT
cana-6092	224	9	,	,	PUNCT
cana-6092	224	10	5595–5637	5595–5637	NUM
cana-6092	224	11	.	.	PUNCT
cana-6092	224	12	30	30	NUM
cana-6092	224	13	.	.	X
cana-6092	225	1	de	de	PROPN
cana-6092	225	2	avila	avila	PROPN
cana-6092	225	3	belbute	belbute	PROPN
cana-6092	225	4	-	-	PUNCT
cana-6092	225	5	peres	peres	PROPN
cana-6092	225	6	,	,	PUNCT
cana-6092	225	7	f.	f.	PROPN
cana-6092	225	8	,	,	PUNCT
cana-6092	225	9	smith	smith	PROPN
cana-6092	225	10	,	,	PUNCT
cana-6092	225	11	k.	k.	PROPN
cana-6092	225	12	,	,	PUNCT
cana-6092	225	13	allen	allen	PROPN
cana-6092	225	14	,	,	PUNCT
cana-6092	225	15	k.	k.	PROPN
cana-6092	225	16	,	,	PUNCT
cana-6092	225	17	tenenbaum	tenenbaum	PROPN
cana-6092	225	18	,	,	PUNCT
cana-6092	225	19	j.	j.	PROPN
cana-6092	225	20	,	,	PUNCT
cana-6092	225	21	&	&	CCONJ
cana-6092	225	22	kolter	kolter	PROPN
cana-6092	225	23	,	,	PUNCT
cana-6092	225	24	j.	j.	PROPN
cana-6092	225	25	z.	z.	PROPN
cana-6092	225	26	(	(	PUNCT
cana-6092	225	27	2018	2018	NUM
cana-6092	225	28	)	)	PUNCT
cana-6092	225	29	.	.	PUNCT
cana-6092	226	1	end	end	NOUN
cana-6092	226	2	-	-	PUNCT
cana-6092	226	3	to	to	ADP
cana-6092	226	4	-	-	PUNCT
cana-6092	226	5	end	end	NOUN
cana-6092	226	6	differentiable	differentiable	ADJ
cana-6092	226	7	physics	physics	NOUN
cana-6092	226	8	for	for	ADP
cana-6092	226	9	learning	learning	NOUN
cana-6092	226	10	and	and	CCONJ
cana-6092	226	11	control	control	NOUN
cana-6092	226	12	.	.	PUNCT
cana-6092	227	1	advances	advance	NOUN
cana-6092	227	2	in	in	ADP
cana-6092	227	3	neural	neural	ADJ
cana-6092	227	4	information	information	NOUN
cana-6092	227	5	processing	processing	NOUN
cana-6092	227	6	systems	system	NOUN
cana-6092	227	7	,	,	PUNCT
cana-6092	227	8	31	31	NUM
cana-6092	227	9	.	.	PUNCT
cana-6092	227	10	31	31	NUM
cana-6092	227	11	.	.	PUNCT
cana-6092	228	1	bengio	bengio	PROPN
cana-6092	228	2	,	,	PUNCT
cana-6092	228	3	y.	y.	PROPN
cana-6092	228	4	,	,	PUNCT
cana-6092	228	5	louradour	louradour	NOUN
cana-6092	228	6	,	,	PUNCT
cana-6092	228	7	j.	j.	PROPN
cana-6092	228	8	,	,	PUNCT
cana-6092	228	9	collobert	collobert	PROPN
cana-6092	228	10	,	,	PUNCT
cana-6092	228	11	r.	r.	PROPN
cana-6092	228	12	,	,	PUNCT
cana-6092	228	13	&	&	CCONJ
cana-6092	228	14	weston	weston	PROPN
cana-6092	228	15	,	,	PUNCT
cana-6092	228	16	j.	j.	PROPN
cana-6092	228	17	(	(	PUNCT
cana-6092	228	18	2009	2009	NUM
cana-6092	228	19	)	)	PUNCT
cana-6092	228	20	.	.	PUNCT
cana-6092	229	1	curriculum	curriculum	NOUN
cana-6092	229	2	learning	learn	VERB
cana-6092	229	3	.	.	PUNCT
cana-6092	230	1	in	in	ADP
cana-6092	230	2	proceedings	proceeding	NOUN
cana-6092	230	3	of	of	ADP
cana-6092	230	4	the	the	DET
cana-6092	230	5	26th	26th	ADJ
cana-6092	230	6	annual	annual	ADJ
cana-6092	230	7	international	international	ADJ
cana-6092	230	8	conference	conference	NOUN
cana-6092	230	9	on	on	ADP
cana-6092	230	10	machine	machine	NOUN
cana-6092	230	11	learning	learning	NOUN
cana-6092	230	12	(	(	PUNCT
cana-6092	230	13	pp	pp	ADJ
cana-6092	230	14	.	.	PUNCT
cana-6092	231	1	41–48	41–48	NUM
cana-6092	231	2	)	)	PUNCT
cana-6092	231	3	.	.	PUNCT
cana-6092	232	1	32	32	NUM
cana-6092	232	2	.	.	X
cana-6092	233	1	zhang	zhang	PROPN
cana-6092	233	2	,	,	PUNCT
cana-6092	233	3	y.	y.	PROPN
cana-6092	233	4	,	,	PUNCT
cana-6092	233	5	&	&	CCONJ
cana-6092	233	6	yang	yang	PROPN
cana-6092	233	7	,	,	PUNCT
cana-6092	233	8	q.	q.	PROPN
cana-6092	233	9	(	(	PUNCT
cana-6092	233	10	2021	2021	NUM
cana-6092	233	11	)	)	PUNCT
cana-6092	233	12	.	.	PUNCT
cana-6092	234	1	a	a	DET
cana-6092	234	2	survey	survey	NOUN
cana-6092	234	3	on	on	ADP
cana-6092	234	4	multi	multi	ADJ
cana-6092	234	5	-	-	ADJ
cana-6092	234	6	task	task	ADJ
cana-6092	234	7	learning	learning	NOUN
cana-6092	234	8	.	.	PUNCT
cana-6092	235	1	ieee	ieee	NOUN
cana-6092	235	2	transactions	transaction	NOUN
cana-6092	235	3	on	on	ADP
cana-6092	235	4	knowledge	knowledge	NOUN
cana-6092	235	5	and	and	CCONJ
cana-6092	235	6	data	datum	NOUN
cana-6092	235	7	engineering	engineering	NOUN
cana-6092	235	8	,	,	PUNCT
cana-6092	235	9	34(12	34(12	NUM
cana-6092	235	10	)	)	PUNCT
cana-6092	235	11	,	,	PUNCT
cana-6092	235	12	5586–5609	5586–5609	NUM
cana-6092	235	13	.	.	PUNCT
cana-6092	236	1	33	33	NUM
cana-6092	236	2	.	.	PUNCT
cana-6092	236	3	kingma	kingma	PROPN
cana-6092	236	4	,	,	PUNCT
cana-6092	236	5	d.	d.	PROPN
cana-6092	236	6	p.	p.	PROPN
cana-6092	236	7	,	,	PUNCT
cana-6092	236	8	&	&	CCONJ
cana-6092	236	9	welling	well	VERB
cana-6092	236	10	,	,	PUNCT
cana-6092	236	11	m.	m.	NOUN
cana-6092	236	12	(	(	PUNCT
cana-6092	236	13	2013	2013	NUM
cana-6092	236	14	)	)	PUNCT
cana-6092	236	15	.	.	PUNCT
cana-6092	237	1	auto	auto	NOUN
cana-6092	237	2	-	-	PUNCT
cana-6092	237	3	encoding	encode	VERB
cana-6092	237	4	variational	variational	ADJ
cana-6092	237	5	bayes	baye	NOUN
cana-6092	237	6	.	.	PUNCT
cana-6092	238	1	arxiv	arxiv	PROPN
cana-6092	238	2	preprint	preprint	NOUN
cana-6092	238	3	arxiv:1312.6114	arxiv:1312.6114	NOUN
cana-6092	238	4	.	.	PUNCT
cana-6092	239	1	34	34	NUM
cana-6092	239	2	.	.	X
cana-6092	239	3	jumper	jumper	PROPN
cana-6092	239	4	,	,	PUNCT
cana-6092	239	5	j.	j.	PROPN
cana-6092	239	6	,	,	PUNCT
cana-6092	239	7	evans	evans	PROPN
cana-6092	239	8	,	,	PUNCT
cana-6092	239	9	r.	r.	PROPN
cana-6092	239	10	,	,	PUNCT
cana-6092	239	11	pritzel	pritzel	NOUN
cana-6092	239	12	,	,	PUNCT
cana-6092	239	13	a.	a.	NOUN
cana-6092	239	14	,	,	PUNCT
cana-6092	239	15	green	green	ADJ
cana-6092	239	16	,	,	PUNCT
cana-6092	239	17	t.	t.	PROPN
cana-6092	239	18	,	,	PUNCT
cana-6092	239	19	figurnov	figurnov	PROPN
cana-6092	239	20	,	,	PUNCT
cana-6092	239	21	m.	m.	NOUN
cana-6092	239	22	,	,	PUNCT
cana-6092	239	23	ronneberger	ronneberger	NOUN
cana-6092	239	24	,	,	PUNCT
cana-6092	239	25	o.	o.	PROPN
cana-6092	239	26	,	,	PUNCT
cana-6092	239	27	...	...	PUNCT
cana-6092	239	28	&	&	CCONJ
cana-6092	239	29	hassabis	hassabis	PROPN
cana-6092	239	30	,	,	PUNCT
cana-6092	239	31	d.	d.	PROPN
cana-6092	239	32	(	(	PUNCT
cana-6092	239	33	2021	2021	NUM
cana-6092	239	34	)	)	PUNCT
cana-6092	239	35	.	.	PUNCT
cana-6092	240	1	highly	highly	ADV
cana-6092	240	2	accurate	accurate	ADJ
cana-6092	240	3	protein	protein	NOUN
cana-6092	240	4	structure	structure	NOUN
cana-6092	240	5	prediction	prediction	NOUN
cana-6092	240	6	with	with	ADP
cana-6092	240	7	alphafold	alphafold	ADJ
cana-6092	240	8	.	.	PUNCT
cana-6092	241	1	nature	nature	NOUN
cana-6092	241	2	,	,	PUNCT
cana-6092	241	3	596(7873	596(7873	NUM
cana-6092	241	4	)	)	PUNCT
cana-6092	241	5	,	,	PUNCT
cana-6092	241	6	583–589	583–589	NUM
cana-6092	241	7	.	.	PUNCT
cana-6092	242	1	35	35	NUM
cana-6092	242	2	.	.	PUNCT
cana-6092	243	1	chen	chen	PROPN
cana-6092	243	2	,	,	PUNCT
cana-6092	243	3	t.	t.	PROPN
cana-6092	243	4	,	,	PUNCT
cana-6092	243	5	kornblith	kornblith	PROPN
cana-6092	243	6	,	,	PUNCT
cana-6092	243	7	s.	s.	PROPN
cana-6092	243	8	,	,	PUNCT
cana-6092	243	9	norouzi	norouzi	PROPN
cana-6092	243	10	,	,	PUNCT
cana-6092	243	11	m.	m.	NOUN
cana-6092	243	12	,	,	PUNCT
cana-6092	243	13	&	&	CCONJ
cana-6092	243	14	hinton	hinton	PROPN
cana-6092	243	15	,	,	PUNCT
cana-6092	243	16	g.	g.	PROPN
cana-6092	243	17	(	(	PUNCT
cana-6092	243	18	2020	2020	NUM
cana-6092	243	19	)	)	PUNCT
cana-6092	243	20	.	.	PUNCT
cana-6092	244	1	a	a	DET
cana-6092	244	2	simple	simple	ADJ
cana-6092	244	3	framework	framework	NOUN
cana-6092	244	4	for	for	ADP
cana-6092	244	5	contrastive	contrastive	ADJ
cana-6092	244	6	learning	learning	NOUN
cana-6092	244	7	of	of	ADP
cana-6092	244	8	visual	visual	ADJ
cana-6092	244	9	representations	representation	NOUN
cana-6092	244	10	.	.	PUNCT
cana-6092	245	1	in	in	ADP
cana-6092	245	2	international	international	ADJ
cana-6092	245	3	conference	conference	NOUN
cana-6092	245	4	on	on	ADP
cana-6092	245	5	machine	machine	NOUN
cana-6092	245	6	learning	learning	NOUN
cana-6092	245	7	(	(	PUNCT
cana-6092	245	8	pp	pp	ADJ
cana-6092	245	9	.	.	PUNCT
cana-6092	245	10	1597–1607	1597–1607	NUM
cana-6092	245	11	)	)	PUNCT
cana-6092	245	12	.	.	PUNCT
cana-6092	246	1	pmlr	pmlr	NOUN
cana-6092	246	2	.	.	PUNCT
cana-6092	247	1	36	36	NUM
cana-6092	247	2	.	.	X
cana-6092	248	1	richardson	richardson	PROPN
cana-6092	248	2	,	,	PUNCT
cana-6092	248	3	a.	a.	PROPN
cana-6092	248	4	(	(	PUNCT
cana-6092	248	5	2018	2018	NUM
cana-6092	248	6	)	)	PUNCT
cana-6092	248	7	.	.	PUNCT
cana-6092	249	1	seismic	seismic	ADJ
cana-6092	249	2	full	full	ADJ
cana-6092	249	3	-	-	PUNCT
cana-6092	249	4	waveform	waveform	NOUN
cana-6092	249	5	inversion	inversion	NOUN
cana-6092	249	6	using	use	VERB
cana-6092	249	7	deep	deep	ADJ
cana-6092	249	8	learning	learning	NOUN
cana-6092	249	9	tools	tool	NOUN
cana-6092	249	10	and	and	CCONJ
cana-6092	249	11	techniques	technique	NOUN
cana-6092	249	12	.	.	PUNCT
cana-6092	250	1	geophysics	geophysic	NOUN
cana-6092	250	2	,	,	PUNCT
cana-6092	250	3	83(1	83(1	PROPN
cana-6092	250	4	)	)	PUNCT
cana-6092	250	5	,	,	PUNCT
cana-6092	250	6	r27	r27	PROPN
cana-6092	250	7	–	–	PUNCT
cana-6092	250	8	r36	r36	NOUN
cana-6092	250	9	.	.	PUNCT
cana-6092	251	1	37	37	NUM
cana-6092	251	2	.	.	PUNCT
cana-6092	252	1	hauptmann	hauptmann	PROPN
cana-6092	252	2	,	,	PUNCT
cana-6092	252	3	a.	a.	PROPN
cana-6092	252	4	,	,	PUNCT
cana-6092	252	5	&	&	CCONJ
cana-6092	252	6	cox	cox	PROPN
cana-6092	252	7	,	,	PUNCT
cana-6092	252	8	b.	b.	PROPN
cana-6092	252	9	t.	t.	PROPN
cana-6092	252	10	(	(	PUNCT
cana-6092	252	11	2020	2020	NUM
cana-6092	252	12	)	)	PUNCT
cana-6092	252	13	.	.	PUNCT
cana-6092	253	1	deep	deep	ADJ
cana-6092	253	2	learning	learning	NOUN
cana-6092	253	3	in	in	ADP
cana-6092	253	4	photoacoustic	photoacoustic	ADJ
cana-6092	253	5	tomography	tomography	NOUN
cana-6092	253	6	:	:	PUNCT
cana-6092	253	7	current	current	ADJ
cana-6092	253	8	approaches	approach	NOUN
cana-6092	253	9	and	and	CCONJ
cana-6092	253	10	future	future	ADJ
cana-6092	253	11	directions	direction	NOUN
cana-6092	253	12	.	.	PUNCT
cana-6092	254	1	journal	journal	NOUN
cana-6092	254	2	of	of	ADP
cana-6092	254	3	biomedical	biomedical	ADJ
cana-6092	254	4	optics	optic	NOUN
cana-6092	254	5	,	,	PUNCT
cana-6092	254	6	25(11	25(11	NUM
cana-6092	254	7	)	)	PUNCT
cana-6092	254	8	,	,	PUNCT
cana-6092	254	9	112903	112903	NUM
cana-6092	254	10	.	.	PUNCT
cana-6092	255	1	38	38	NUM
cana-6092	255	2	.	.	PUNCT
cana-6092	256	1	lustig	lustig	PROPN
cana-6092	256	2	,	,	PUNCT
cana-6092	256	3	m.	m.	NOUN
cana-6092	256	4	,	,	PUNCT
cana-6092	256	5	donoho	donoho	PROPN
cana-6092	256	6	,	,	PUNCT
cana-6092	256	7	d.	d.	PROPN
cana-6092	256	8	,	,	PUNCT
cana-6092	256	9	&	&	CCONJ
cana-6092	256	10	pauly	pauly	PROPN
cana-6092	256	11	,	,	PUNCT
cana-6092	256	12	j.	j.	PROPN
cana-6092	256	13	m.	m.	PROPN
cana-6092	256	14	(	(	PUNCT
cana-6092	256	15	2007	2007	NUM
cana-6092	256	16	)	)	PUNCT
cana-6092	256	17	.	.	PUNCT
cana-6092	257	1	sparse	sparse	ADJ
cana-6092	257	2	mri	mri	NOUN
cana-6092	257	3	:	:	PUNCT
cana-6092	257	4	the	the	DET
cana-6092	257	5	application	application	NOUN
cana-6092	257	6	of	of	ADP
cana-6092	257	7	compressed	compressed	ADJ
cana-6092	257	8	sensing	sensing	NOUN
cana-6092	257	9	for	for	ADP
cana-6092	257	10	rapid	rapid	ADJ
cana-6092	257	11	mr	mr	PROPN
cana-6092	257	12	imaging	imaging	PROPN
cana-6092	257	13	.	.	PUNCT
cana-6092	258	1	magnetic	magnetic	ADJ
cana-6092	258	2	resonance	resonance	NOUN
cana-6092	258	3	in	in	ADP
cana-6092	258	4	medicine	medicine	NOUN
cana-6092	258	5	,	,	PUNCT
cana-6092	258	6	58(6	58(6	NOUN
cana-6092	258	7	)	)	PUNCT
cana-6092	258	8	,	,	PUNCT
cana-6092	258	9	1182–1195	1182–1195	NUM
cana-6092	258	10	.	.	NOUN
cana-6092	258	11	39	39	NUM
cana-6092	258	12	.	.	PUNCT
cana-6092	259	1	wang	wang	PROPN
cana-6092	259	2	,	,	PUNCT
cana-6092	259	3	g.	g.	PROPN
cana-6092	259	4	,	,	PUNCT
cana-6092	259	5	ye	ye	PROPN
cana-6092	259	6	,	,	PUNCT
cana-6092	259	7	j.	j.	PROPN
cana-6092	259	8	c.	c.	PROPN
cana-6092	259	9	,	,	PUNCT
cana-6092	259	10	&	&	CCONJ
cana-6092	259	11	de	de	PROPN
cana-6092	259	12	man	man	PROPN
cana-6092	259	13	,	,	PUNCT
cana-6092	259	14	b.	b.	PROPN
cana-6092	259	15	(	(	PUNCT
cana-6092	259	16	2020	2020	NUM
cana-6092	259	17	)	)	PUNCT
cana-6092	259	18	.	.	PUNCT
cana-6092	260	1	deep	deep	ADJ
cana-6092	260	2	learning	learning	NOUN
cana-6092	260	3	for	for	ADP
cana-6092	260	4	tomographic	tomographic	ADJ
cana-6092	260	5	image	image	NOUN
cana-6092	260	6	reconstruction	reconstruction	NOUN
cana-6092	260	7	.	.	PUNCT
cana-6092	261	1	nature	nature	NOUN
cana-6092	261	2	machine	machine	NOUN
cana-6092	261	3	intelligence	intelligence	NOUN
cana-6092	261	4	,	,	PUNCT
cana-6092	261	5	2(12	2(12	NUM
cana-6092	261	6	)	)	PUNCT
cana-6092	261	7	,	,	PUNCT
cana-6092	261	8	737–748	737–748	NUM
cana-6092	261	9	.	.	PUNCT
cana-6092	262	1	40	40	NUM
cana-6092	262	2	.	.	PUNCT
cana-6092	263	1	rudin	rudin	PROPN
cana-6092	263	2	,	,	PUNCT
cana-6092	263	3	l.	l.	PROPN
cana-6092	263	4	i.	i.	PROPN
cana-6092	263	5	,	,	PUNCT
cana-6092	263	6	osher	osher	PROPN
cana-6092	263	7	,	,	PUNCT
cana-6092	263	8	s.	s.	PROPN
cana-6092	263	9	,	,	PUNCT
cana-6092	263	10	&	&	CCONJ
cana-6092	263	11	fatemi	fatemi	PROPN
cana-6092	263	12	,	,	PUNCT
cana-6092	263	13	e.	e.	PROPN
cana-6092	263	14	(	(	PUNCT
cana-6092	263	15	1992	1992	NUM
cana-6092	263	16	)	)	PUNCT
cana-6092	263	17	.	.	PUNCT
cana-6092	264	1	nonlinear	nonlinear	ADJ
cana-6092	264	2	total	total	ADJ
cana-6092	264	3	variation	variation	NOUN
cana-6092	264	4	based	base	VERB
cana-6092	264	5	noise	noise	NOUN
cana-6092	264	6	removal	removal	NOUN
cana-6092	264	7	algorithms	algorithm	NOUN
cana-6092	264	8	.	.	PUNCT
cana-6092	265	1	physica	physica	NOUN
cana-6092	265	2	d	d	NOUN
cana-6092	265	3	:	:	PUNCT
cana-6092	265	4	nonlinear	nonlinear	ADJ
cana-6092	265	5	phenomena	phenomenon	NOUN
cana-6092	265	6	,	,	PUNCT
cana-6092	265	7	60(1	60(1	NUM
cana-6092	265	8	-	-	SYM
cana-6092	265	9	4	4	NUM
cana-6092	265	10	)	)	PUNCT
cana-6092	265	11	,	,	PUNCT
cana-6092	265	12	259–268	259–268	NUM
cana-6092	265	13	.	.	PUNCT
cana-6092	266	1	41	41	NUM
cana-6092	266	2	.	.	PUNCT
cana-6092	267	1	hornik	hornik	PROPN
cana-6092	267	2	,	,	PUNCT
cana-6092	267	3	k.	k.	PROPN
cana-6092	267	4	,	,	PUNCT
cana-6092	267	5	stinchcombe	stinchcombe	PROPN
cana-6092	267	6	,	,	PUNCT
cana-6092	267	7	m.	m.	NOUN
cana-6092	267	8	,	,	PUNCT
cana-6092	267	9	&	&	CCONJ
cana-6092	267	10	white	white	PROPN
cana-6092	267	11	,	,	PUNCT
cana-6092	267	12	h.	h.	PROPN
cana-6092	267	13	(	(	PUNCT
cana-6092	267	14	1989	1989	NUM
cana-6092	267	15	)	)	PUNCT
cana-6092	267	16	.	.	PUNCT
cana-6092	268	1	multilayer	multilayer	ADJ
cana-6092	268	2	feedforward	feedforward	NOUN
cana-6092	268	3	networks	network	NOUN
cana-6092	268	4	are	be	AUX
cana-6092	268	5	universal	universal	ADJ
cana-6092	268	6	approximators	approximator	NOUN
cana-6092	268	7	.	.	PUNCT
cana-6092	269	1	neural	neural	ADJ
cana-6092	269	2	networks	network	NOUN
cana-6092	269	3	,	,	PUNCT
cana-6092	269	4	2(5	2(5	NUM
cana-6092	269	5	)	)	PUNCT
cana-6092	269	6	,	,	PUNCT
cana-6092	269	7	359–366	359–366	NUM
cana-6092	269	8	.	.	PUNCT
cana-6092	270	1	communications	communication	NOUN
cana-6092	270	2	on	on	ADP
cana-6092	270	3	applied	apply	VERB
cana-6092	270	4	nonlinear	nonlinear	ADJ
cana-6092	270	5	analysis	analysis	NOUN
cana-6092	270	6	issn	issn	NOUN
cana-6092	270	7	:	:	PUNCT
cana-6092	270	8	1074	1074	NUM
cana-6092	270	9	-	-	PUNCT
cana-6092	270	10	133x	133x	NUM
cana-6092	270	11	vol	vol	NOUN
cana-6092	270	12	31	31	NUM
cana-6092	270	13	no	no	NOUN
cana-6092	270	14	.	.	NOUN
cana-6092	270	15	2	2	NUM
cana-6092	270	16	(	(	PUNCT
cana-6092	270	17	2024	2024	NUM
cana-6092	270	18	)	)	PUNCT
cana-6092	270	19	509	509	NUM
cana-6092	270	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-6092	270	21	42	42	NUM
cana-6092	270	22	.	.	PUNCT
cana-6092	271	1	gal	gal	PROPN
cana-6092	271	2	,	,	PUNCT
cana-6092	271	3	y.	y.	PROPN
cana-6092	271	4	,	,	PUNCT
cana-6092	271	5	&	&	CCONJ
cana-6092	271	6	ghahramani	ghahramani	PROPN
cana-6092	271	7	,	,	PUNCT
cana-6092	271	8	z.	z.	PROPN
cana-6092	271	9	(	(	PUNCT
cana-6092	271	10	2016	2016	NUM
cana-6092	271	11	)	)	PUNCT
cana-6092	271	12	.	.	PUNCT
cana-6092	272	1	dropout	dropout	NOUN
cana-6092	272	2	as	as	ADP
cana-6092	272	3	a	a	DET
cana-6092	272	4	bayesian	bayesian	NOUN
cana-6092	272	5	approximation	approximation	NOUN
cana-6092	272	6	:	:	PUNCT
cana-6092	272	7	representing	represent	VERB
cana-6092	272	8	model	model	NOUN
cana-6092	272	9	uncertainty	uncertainty	NOUN
cana-6092	272	10	in	in	ADP
cana-6092	272	11	deep	deep	ADJ
cana-6092	272	12	learning	learning	NOUN
cana-6092	272	13	.	.	PUNCT
cana-6092	273	1	in	in	ADP
cana-6092	273	2	international	international	ADJ
cana-6092	273	3	conference	conference	NOUN
cana-6092	273	4	on	on	ADP
cana-6092	273	5	machine	machine	NOUN
cana-6092	273	6	learning	learning	NOUN
cana-6092	273	7	(	(	PUNCT
cana-6092	273	8	pp	pp	ADJ
cana-6092	273	9	.	.	PUNCT
cana-6092	274	1	1050–1059	1050–1059	NUM
cana-6092	274	2	)	)	PUNCT
cana-6092	274	3	.	.	PUNCT
cana-6092	275	1	pmlr	pmlr	NOUN
cana-6092	275	2	.	.	PUNCT
cana-6092	276	1	43	43	NUM
cana-6092	276	2	.	.	PUNCT
cana-6092	277	1	hinton	hinton	PROPN
cana-6092	277	2	,	,	PUNCT
cana-6092	277	3	g.	g.	PROPN
cana-6092	277	4	,	,	PUNCT
cana-6092	277	5	vinyals	vinyal	NOUN
cana-6092	277	6	,	,	PUNCT
cana-6092	277	7	o.	o.	NOUN
cana-6092	277	8	,	,	PUNCT
cana-6092	277	9	&	&	CCONJ
cana-6092	277	10	dean	dean	PROPN
cana-6092	277	11	,	,	PUNCT
cana-6092	277	12	j.	j.	PROPN
cana-6092	277	13	(	(	PUNCT
cana-6092	277	14	2015	2015	NUM
cana-6092	277	15	)	)	PUNCT
cana-6092	277	16	.	.	PUNCT
cana-6092	278	1	distilling	distil	VERB
cana-6092	278	2	the	the	DET
cana-6092	278	3	knowledge	knowledge	NOUN
cana-6092	278	4	in	in	ADP
cana-6092	278	5	a	a	DET
cana-6092	278	6	neural	neural	ADJ
cana-6092	278	7	network	network	NOUN
cana-6092	278	8	.	.	PUNCT
cana-6092	279	1	arxiv	arxiv	PROPN
cana-6092	279	2	preprint	preprint	NOUN
cana-6092	279	3	arxiv:1503.02531	arxiv:1503.02531	PROPN
cana-6092	279	4	.	.	PUNCT
cana-6092	280	1	44	44	NUM
cana-6092	280	2	.	.	PUNCT
cana-6092	281	1	han	han	PROPN
cana-6092	281	2	,	,	PUNCT
cana-6092	281	3	j.	j.	PROPN
cana-6092	281	4	,	,	PUNCT
cana-6092	281	5	jentzen	jentzen	PROPN
cana-6092	281	6	,	,	PUNCT
cana-6092	281	7	a.	a.	NOUN
cana-6092	281	8	,	,	PUNCT
cana-6092	281	9	&	&	CCONJ
cana-6092	281	10	e	e	PROPN
cana-6092	281	11	,	,	PUNCT
cana-6092	281	12	w.	w.	PROPN
cana-6092	281	13	(	(	PUNCT
cana-6092	281	14	2018	2018	NUM
cana-6092	281	15	)	)	PUNCT
cana-6092	281	16	.	.	PUNCT
cana-6092	282	1	solving	solve	VERB
cana-6092	282	2	high	high	ADJ
cana-6092	282	3	-	-	PUNCT
cana-6092	282	4	dimensional	dimensional	ADJ
cana-6092	282	5	partial	partial	ADJ
cana-6092	282	6	differential	differential	NOUN
cana-6092	282	7	equations	equation	NOUN
cana-6092	282	8	using	use	VERB
cana-6092	282	9	deep	deep	ADJ
cana-6092	282	10	learning	learning	NOUN
cana-6092	282	11	.	.	PUNCT
cana-6092	283	1	proceedings	proceeding	NOUN
cana-6092	283	2	of	of	ADP
cana-6092	283	3	the	the	DET
cana-6092	283	4	national	national	PROPN
cana-6092	283	5	academy	academy	PROPN
cana-6092	283	6	of	of	ADP
cana-6092	283	7	sciences	sciences	PROPN
cana-6092	283	8	,	,	PUNCT
cana-6092	283	9	115(34	115(34	NUM
cana-6092	283	10	)	)	PUNCT
cana-6092	283	11	,	,	PUNCT
cana-6092	283	12	8505–8510	8505–8510	NUM
cana-6092	283	13	.	.	NOUN
cana-6092	283	14	45	45	NUM
cana-6092	283	15	.	.	NOUN
cana-6092	283	16	bleistein	bleistein	NOUN
cana-6092	283	17	,	,	PUNCT
cana-6092	283	18	n.	n.	PROPN
cana-6092	283	19	,	,	PUNCT
cana-6092	283	20	cohen	cohen	PROPN
cana-6092	283	21	,	,	PUNCT
cana-6092	283	22	j.	j.	PROPN
cana-6092	283	23	k.	k.	PROPN
cana-6092	283	24	,	,	PUNCT
cana-6092	283	25	&	&	CCONJ
cana-6092	283	26	stockwell	stockwell	PROPN
cana-6092	283	27	,	,	PUNCT
cana-6092	283	28	j.	j.	PROPN
cana-6092	283	29	w.	w.	PROPN
cana-6092	283	30	(	(	PUNCT
cana-6092	283	31	2001	2001	NUM
cana-6092	283	32	)	)	PUNCT
cana-6092	283	33	.	.	PUNCT
cana-6092	284	1	mathematics	mathematic	NOUN
cana-6092	284	2	of	of	ADP
cana-6092	284	3	multidimensional	multidimensional	ADJ
cana-6092	284	4	seismic	seismic	ADJ
cana-6092	284	5	imaging	imaging	NOUN
cana-6092	284	6	,	,	PUNCT
cana-6092	284	7	migration	migration	NOUN
cana-6092	284	8	,	,	PUNCT
cana-6092	284	9	and	and	CCONJ
cana-6092	284	10	inversion	inversion	NOUN
cana-6092	284	11	.	.	PUNCT
cana-6092	285	1	springer	springer	NOUN
cana-6092	285	2	science	science	PROPN
cana-6092	285	3	&	&	CCONJ
cana-6092	285	4	business	business	NOUN
cana-6092	285	5	media	medium	NOUN
cana-6092	285	6	.	.	PUNCT