35 citations · 35 across the 2 of their papers we have counts for
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cs.LG2024
Advancing Generalization in PINNs through Latent-Space Representations
Honghui Wang, Yifan Pu, Shiji Song +1
Physics-informed neural networks (PINNs) have made significant strides in modeling dynamical systems governed by partial differential equations (PDEs). However, their generalizatio…
cs.LG2023★ 35 cited
Learning Specialized Activation Functions for Physics-informed Neural Networks
Honghui Wang, Lu Lu, Shiji Song +1
Physics-informed neural networks (PINNs) are known to suffer from optimization difficulty. In this work, we reveal the connection between the optimization difficulty of PINNs and a…