Unlearning Noise in PINNs: A Selective Pruning Framework for PDE Inverse Problems
arXiv:2602.19967v3 Announce Type: replace
Abstract: Physics-informed neural networks (PINNs) provide a promising framework for solving inverse problems governed by partial differential equations (PDEs) by integrating observational data and physical co…