2026
Heavy-tailed Physics-Informed Neural Networks
Jephte Abijuru, Mayank Kumar Nagda, Phil Sidney Ostheimer, Jan Tauberschmidt, Sebastian Vollmer, Stephan Mandt +2
ICML 2026poster
Physics-informed neural networks (PINNs) enforce physical laws by minimizing partial differential equation (PDE) residuals and auxiliary constraints. Standard training relies on a mean-squared error (MSE) objective, which implicitly assumes independent Gaussian residuals with a fixed global variance…