A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Chenxi Wu, Min Zhu, Qinyang Tan +2

Physics-informed neural networks (PINNs) have shown to be an effective tool for solving forward and inverse problems of partial differential equations (PDEs). PINNs embed the PDEs…