Guiding continuous operator learning through Physics-based boundary
constraints

Guiding continuous operator learning through Physics-based boundary constraints

14 December 2022

Gaurav Gupta

Danielle C. Maddix

Papers citing "Guiding continuous operator learning through Physics-based boundary constraints"

8 / 8 papers shown

Title
Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics Matthias Karlbauer Danielle C. Maddix Abdul Fatir Ansari Boran Han Gaurav Gupta Yuyang Wang Andrew Stuart Michael W. Mahoney AI4TS 42 1 0 19 Jul 2024
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 18 9 0 08 Oct 2023
PreDiff: Precipitation Nowcasting with Latent Diffusion Models Zhihan Gao Xingjian Shi Boran Han Hongya Wang Xiaoyong Jin Danielle C. Maddix Yi Zhu Mu Li Bernie Wang BDL DiffM 23 54 0 19 Jul 2023
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 31 3 0 25 Nov 2022
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 124 200 0 28 Sep 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 493 0 09 Feb 2021
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 203 2,272 0 18 Oct 2020
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework C. Jiang S. Esmaeilzadeh Kamyar Azizzadenesheli K. Kashinath Mustafa A. Mustafa H. Tchelepi P. Marcus P. Prabhat Anima Anandkumar AI4CE 182 140 0 01 May 2020