13 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics
Lu Zhang, Huaiqian You, Tian Gao +3
Gradient-based meta-learning methods have primarily been applied to classical machine learning tasks such as image classification. Recently, PDE-solving deep learning methods, such…
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…
cs.LG2022★ 13 cited
Physics-Informed Deep Neural Operator Networks
Somdatta Goswami, Aniruddha Bora, Yue Yu +1
Standard neural networks can approximate general nonlinear operators, represented either explicitly by a combination of mathematical operators, e.g., in an advection-diffusion-reac…