Recommending several papers

[smao-astro]

Great job! I wish that I had seen this earlier.

I would like to recommend

1. When and why PINNs fail to train: A neural tangent kernel perspective
2. On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
3. Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
4. Long-time integration of parametric evolution equations with physics-informed DeepONets

[vaishnavtv]

Can I also recommend this paper on an Active Learning strategy for generating collocation points in PINNs?
Optimal Transport Based Refinement of Physics-Informed Neural Networks