id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cord-243070-0b06zk1q	Lesniewski, Andrew	Epidemic control via stochastic optimal control	2020-04-14		.txt	text/plain	3793	199	57	Population biology of infectious diseases: Part I Dynamic Programming Time-optimal control strategies in SIR epidemic models Mathematical Models in Epidemiology Stochastic epidemic models: A survey Deterministic and stochastic models for recurrent epidemics Discrete Time Approximation and Monte-Carlo Simulation of Backward Stochastic Differential Equations, Stochastic Processes and their Applications A Scandal in Bohemia, (1891), included in The Adventures of Sherlock Holmes Backward stochastic differential equations in finance Controlled Markov processes and viscosity solutions A stochastic differential equation SIS epidemic model Geometric numerical integration illustrated by the StörmerVerlet method Optimal control of epidemics with limited resources Solving high-dimensional partial differential equations using deep learning A contribution to the mathematical theory of epidemics Stochastic Stability of Differential Equations Simulating Hamiltonian Dynamics Options on infectious diseases Managing counterparty credit risk via backward stochastic differential equations Valuing American Options by Simulation: A Simple Least-Squares Approach Continuous-time Stochastic Control and Optimization with Financial Applications The Mathematical Theory of Optimal Processes Stochastic Controls: Hamiltonian Systems and HJB Equations This leads to the following system of stochastic differential equations (SDE), driven by W t with the initial conditions The third component of the process, X 3 = R, follows the dynamics which implies that the conservation law continues to hold in the stochastic model.	cache/cord-243070-0b06zk1q.txt	txt/cord-243070-0b06zk1q.txt
