Neural Spectral Methods: Self-supervised learning in the spectral domain

8 December 2023

Papers citing "Neural Spectral Methods: Self-supervised learning in the spectral domain"

8 / 8 papers shown

Title
$M$^{2}$M: Learning controllable Multi of experts and multi-scale operators are the Partial Differential Equations need$ M $^{2}$ M: Learning controllable Multi of experts and multi-scale operators are the Partial Differential Equations need Aoming Liang Zhaoyang Mu Pengxiao Lin Cong Wang Mingming Ge Ling Shao Dixia Fan Hao Tang AI4CE 31 0 0 01 Oct 2024
Solving partial differential equations with sampled neural networks Chinmay Datar Taniya Kapoor Abhishek Chandra Qing Sun Iryna Burak Erik Lien Bolager Anna Veselovska Massimo Fornasier Felix Dietrich 40 2 0 31 May 2024
Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement Hongwei Jin Prasanna Balaprakash Allen Zou Pieter Ghysels Aditi S. Krishnapriyan Adam Mate Arthur Barnes Russell Bent AI4CE 32 1 0 16 May 2024
Scaling physics-informed hard constraints with mixture-of-experts N. Chalapathi Yiheng Du Aditi Krishnapriyan AI4CE 40 12 0 20 Feb 2024
Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations Ramansh Sharma Varun Shankar 43 40 0 19 May 2022
Multiwavelet-based Operator Learning for Differential Equations Gaurav Gupta Xiongye Xiao P. Bogdan 126 202 0 28 Sep 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 131 439 0 18 Dec 2020
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 259 2,298 0 18 Oct 2020