Separable Physics-Informed Neural Networks

Separable Physics-Informed Neural Networks

28 June 2023

Papers citing "Separable Physics-Informed Neural Networks"

10 / 10 papers shown

Title
Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs Sidharth S. Menon Ameya D. Jagtap PINN 104 0 0 06 May 2025
Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks Yequan Zhao Xinling Yu Xian Xiao Z. Chen Z. Liu G. Kurczveil R. Beausoleil S. Liu Z. Zhang 49 0 0 17 Feb 2025
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks Youngsik Hwang Dong-Young Lim AI4CE 28 2 0 27 Sep 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 38 1 0 09 May 2024
KAN: Kolmogorov-Arnold Networks Ziming Liu Yixuan Wang Sachin Vaidya Fabian Ruehle James Halverson Marin Soljacic Thomas Y. Hou Max Tegmark 72 470 0 30 Apr 2024
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zong-Yi Li Daniel Zhengyu Huang Burigede Liu Anima Anandkumar AI4CE 108 249 0 11 Jul 2022
Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations Ramansh Sharma Varun Shankar 27 40 0 19 May 2022
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 50 59 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 40 209 0 16 Jul 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