PDE-Net: Learning PDEs from Data

26 October 2017

Papers citing "PDE-Net: Learning PDEs from Data"

9 / 9 papers shown

Title
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 128 0 0 02 Mar 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 97 1 0 15 Dec 2024
Generating synthetic data for neural operators Erisa Hasani Rachel A. Ward AI4CE 90 8 0 04 Jan 2024
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction Hao Wu Wei Xion Fan Xu Xian-Sheng Hua C. L. Philip Chen Xiansheng Hua AI4TS 120 28 0 19 May 2023
Integration of knowledge and data in machine learning Yuntian Chen Dongxiao Zhang PINN 44 32 0 15 Feb 2022
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 148 49 0 27 Feb 2020
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge Emmanuel de Bézenac Arthur Pajot Patrick Gallinari PINN AI4CE 47 319 0 21 Nov 2017
Hidden Physics Models: Machine Learning of Nonlinear Partial Differential Equations M. Raissi George Karniadakis AI4CE PINN 55 1,134 0 02 Aug 2017
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 288 10,149 0 16 Mar 2016