Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
The residual loss in Physics-Informed Neural Networks (PINNs) alters the simple recursive relation of layers in a feed-forward neural network by applying a differential operator, resulting in a loss landscape that is inherently different from those of common supervised problems. Therefore, relying on the existing theory leads to unjustified design …