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Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws

18 December 2023

Papers citing "Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws"

23 / 23 papers shown

Title
Deep Neural Operator Enabled Digital Twin Modeling for Additive Manufacturing Ning Liu Xuxiao Li M. Rajanna E. Reutzel Brady A Sawyer Prahalada Rao Jim Lua Nam Phan Yue Yu AI4CE 76 9 0 13 May 2024
Domain Agnostic Fourier Neural Operators Ning Liu S. Jafarzadeh Yue Yu AI4CE 125 26 0 30 Apr 2023
Koopman neural operator as a mesh-free solver of non-linear partial differential equations Wei Xiong Xiaomeng Huang Ziyang Zhang Ruixuan Deng Pei Sun Yang Tian AI4CE 69 34 0 24 Jan 2023
Guiding continuous operator learning through Physics-based boundary constraints Nadim Saad Gaurav Gupta S. Alizadeh Danielle C. Maddix AI4CE 105 22 0 14 Dec 2022
Fourier Continuation for Exact Derivative Computation in Physics-Informed Neural Operators Ha Maust Zong-Yi Li Yixuan Wang Daniel Leibovici O. Bruno T. Hou Anima Anandkumar AI4CE 60 12 0 29 Nov 2022
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning M. Takamoto T. Praditia Raphael Leiteritz Dan MacKinlay Francesco Alesiani Dirk Pflüger Mathias Niepert AI4CE 72 237 0 13 Oct 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 103 56 0 04 Oct 2022
Exact conservation laws for neural network integrators of dynamical systems E. Müller PINN 105 14 0 23 Sep 2022
Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling Huaiqian You Quinn Zhang Colton J. Ross Chung-Hao Lee Yue Yu AI4CE 91 107 0 15 Mar 2022
IAE-Net: Integral Autoencoders for Discretization-Invariant Learning Yong Zheng Ong Zuowei Shen Haizhao Yang 77 16 0 10 Mar 2022
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 121 424 0 06 Nov 2021
Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs Fang Wu Dragomir R. Radev Huabin Xing ViT 90 58 0 04 Oct 2021
Data-driven Tissue Mechanics with Polyconvex Neural Ordinary Differential Equations Vahidullah Tac F. Sahli Costabal A. B. Tepole AI4CE 97 71 0 03 Oct 2021
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 191 220 0 28 Sep 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review Shengze Cai Zhiping Mao Zhicheng Wang Minglang Yin George Karniadakis PINN AI4CE 85 1,201 0 20 May 2021
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets Sizhuang He Hanwen Wang P. Perdikaris AI4CE 97 707 0 19 Mar 2021
E(n) Equivariant Graph Neural Networks Victor Garcia Satorras Emiel Hoogeboom Max Welling 113 1,035 0 19 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 504 2,453 0 18 Oct 2020
Learning Mesh-Based Simulation with Graph Networks Tobias Pfaff Meire Fortunato Alvaro Sanchez-Gonzalez Peter W. Battaglia AI4CE 82 806 0 07 Oct 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 175 437 0 10 Mar 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar 202 748 0 07 Mar 2020
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,158 0 08 Oct 2019
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks David Pfau J. Spencer A. G. Matthews W. Foulkes 84 465 0 05 Sep 2019