Learning black-and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data
We propose a machine learning framework for the data-driven discovery of macroscopic
chemotactic Partial Differential Equations (PDEs)—and the closures that lead to them-from …
chemotactic Partial Differential Equations (PDEs)—and the closures that lead to them-from …
Integrating inverse reinforcement learning into data-driven mechanistic computational models: a novel paradigm to decode cancer cell heterogeneity
Cellular heterogeneity is a ubiquitous aspect of biology and a major obstacle to successful
cancer treatment. Several techniques have emerged to quantify heterogeneity in live cells …
cancer treatment. Several techniques have emerged to quantify heterogeneity in live cells …