Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data

DOI10.1007/s00285-023-01946-0zbMath1521.92007arXiv2205.13545MaRDI QIDQ6110192

Seung Joon Lee, Constantinos I. Siettos, Unnamed Author, Ioannis G. Kevrekidis

Publication date: 4 July 2023

Published in: Journal of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2205.13545

zbMATH Keywords

inverse problemschemotaxisstochastic simulationspartial differential equationsmachine learningnumerical analysismultiscale methods

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Learning and adaptive systems in artificial intelligence (68T05) Dynamical systems in biology (37N25) PDEs in connection with biology, chemistry and other natural sciences (35Q92) Inverse problems for PDEs (35R30) Numerical solutions to stochastic differential and integral equations (65C30) Computational methods for problems pertaining to biology (92-08) Cell movement (chemotaxis, etc.) (92C17)

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