LordNet: An Efficient Neural Network for Learning to Solve Parametric
Partial Differential Equations without Simulated Data

LordNet: An Efficient Neural Network for Learning to Solve Parametric Partial Differential Equations without Simulated Data

19 June 2022

Jiang Bian

Papers citing "LordNet: An Efficient Neural Network for Learning to Solve Parametric Partial Differential Equations without Simulated Data"

7 / 7 papers shown

Title
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition Xinquan Huang Wenlei Shi Qi Meng Yue Wang Xiaotian Gao Jia Zhang Tie-Yan Liu AI4CE 21 8 0 20 Feb 2023
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 60 79 0 08 Sep 2022
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 50 58 0 15 Sep 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 40 207 0 16 Jul 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 239 2,600 0 04 May 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 2,281 0 18 Oct 2020
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 144 445 0 16 Sep 2019