Auxiliary Finite-Difference Residual-Gradient Regularization for PINNs
arXiv:2604.14472v1 Announce Type: new
Abstract: Physics-informed neural networks (PINNs) are often selected by a single scalar loss even when the quantity of interest is more specific. We study a hybrid design in which the governing PDE residual remai…