most citedPirateNets: Physics-informed Deep Learning with Residual Adaptive Networks

25 citations · 25 across the 3 of their papers we have counts for

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cs.LG2025

Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective

Sifan Wang, Ananyae Kumar Bhartari, Bowen Li +1

Multi-task learning through composite loss functions is fundamental to modern deep learning, yet optimizing competing objectives remains challenging. We present new theoretical and…

cs.LG2024★ 25 cited

PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks

Sifan Wang, Bowen Li, Yuhan Chen +1

While physics-informed neural networks (PINNs) have become a popular deep learning framework for tackling forward and inverse problems governed by partial differential equations (P…