cs.LG, physics.comp-ph, physics.flu-dyn, stat.ML

Bayesian Reasoning for Physics Informed Neural Networks

arXiv:2308.13222v3 Announce Type: replace-cross
Abstract: We introduce an evidence-driven Bayesian formulation of physics-informed neural networks that enables automatic optimization of loss weights between PDE residuals, boundary conditions, and obse…