Shuang-Qing Chen

Learning approximate solutions of partial differential equations within the physics-informed framework

Variants of physics-informed neural networks (PINNs) often treat neural networks as the main solution representation, yet solutions are encoded implicitly in high-dimensional weights, making training behavior and outcomes difficult to predict or analyze across different partial differential equation (PDE) settings. I...