PirateNets: Physics-informed Deep Learning with Residual Adaptive
Networks
PirateNets: Physics-informed Deep Learning with Residual Adaptive
Networks
While physics-informed neural networks (PINNs) have become a popular deep learning framework for tackling forward and inverse problems governed by partial differential equations (PDEs), their performance is known to degrade when larger and deeper neural network architectures are employed. Our study identifies that the root of this counter-intuitive behavior lies …