14 citations · 30 across the 8 of their papers we have counts for
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cs.LG2023★ 2 cited
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
Ning Liu, Yiming Fan, Xianyi Zeng +3
Neural operators (NOs) have emerged as effective tools for modeling complex physical systems in scientific machine learning. In NOs, a central characteristic is to learn the govern…
cs.LG2023★ 5 cited
Domain Agnostic Fourier Neural Operators
Ning Liu, Siavash Jafarzadeh, Yue Yu
Fourier neural operators (FNOs) can learn highly nonlinear mappings between function spaces, and have recently become a popular tool for learning responses of complex physical syst…
cs.LG2023★ 2 cited
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation
Ning Liu, Yue Yu, Huaiqian You +1
Neural operators, which emerge as implicit solution operators of hidden governing equations, have recently become popular tools for learning responses of complex real-world physica…