53 citations · 149 across the 23 of their papers we have counts for
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cs.LG2023★ 3 cited
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks
Woojin Cho, Kookjin Lee, Donsub Rim +1
In various engineering and applied science applications, repetitive numerical simulations of partial differential equations (PDEs) for varying input parameters are often required (…
cs.LG2023★ 1 cited
Reversible and irreversible bracket-based dynamics for deep graph neural networks
Anthony Gruber, Kookjin Lee, Nathaniel Trask
Recent works have shown that physics-inspired architectures allow the training of deep graph neural networks (GNNs) without oversmoothing. The role of these physics is unclear, how…