Biological and environmental systems rarely present a clean choice between first-principles equations and black-box learning. More often, core mechanisms such as disease progression, conservation relations, reaction stoichiometry, or transport direction are known, while key drivers such as behavior, regulation, unresol...
Hao Wang, Amit K. Chakraborty, Esha Saha· Mathematical Biosciences· 0 citations
This paper proposes a trainable Neural Cellular Automata (NCA) based surrogate model for learning long time PDE dynamics that achieves the lowest long-horizon relative errors on the majority of the experiments.
Esha Saha, Hao Wang· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.