Residual-based attention and connection to information bottleneck theory
in PINNs

Residual-based attention and connection to information bottleneck theory in PINNs

1 July 2023

Sokratis J. Anagnostopoulos

Juan Diego Toscano

Nikos Stergiopulos

George Karniadakis

Papers citing "Residual-based attention and connection to information bottleneck theory in PINNs"

15 / 15 papers shown

Title
Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective Sizhuang He Ananyae Kumar Bhartari Bowen Li P. Perdikaris PINN 56 4 0 02 Feb 2025
MILP initialization for solving parabolic PDEs with PINNs Sirui Li Federica Bragone Matthieu Barreau Kateryna Morozovska 33 0 0 28 Jan 2025
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations Shu Liu Stanley Osher Wuchen Li 28 0 0 09 Nov 2024
Robust Neural IDA-PBC: passivity-based stabilization under approximations Santiago Sanchez-Escalonilla Samuele Zoboli B. Jayawardhana 23 1 0 24 Sep 2024
Physics-Informed Neural Networks and Extensions Maziar Raissi P. Perdikaris Nazanin Ahmadi George Karniadakis PINN AI4CE 41 4 0 29 Aug 2024
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks K. Shukla Juan Diego Toscano Zhicheng Wang Zongren Zou George Karniadakis 48 74 0 05 Jun 2024
Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs Jose Florido He-Nan Wang Amirul Khan P. Jimack 31 2 0 18 Apr 2024
Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradients Rahul Sundar Didier Lucor Sunetra Sarkar AI4CE 21 0 0 27 Feb 2024
Deep adaptive sampling for surrogate modeling without labeled data Xili Wang Keju Tang Jiayu Zhai Xiaoliang Wan Chao Yang 35 2 0 17 Feb 2024
Densely Multiplied Physics Informed Neural Networks Feilong Jiang Xiaonan Hou Min Xia PINN 19 2 0 06 Feb 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks Sizhuang He Bowen Li Yuhan Chen P. Perdikaris AI4CE PINN 26 29 0 01 Feb 2024
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning Qian Zhang Chen-Chun Wu Adar Kahana Youngeun Kim Yuhang Li George Karniadakis Priyadarshini Panda 27 9 0 31 Aug 2023
Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs) S. Basir PINN AI4CE 29 21 0 20 Sep 2022
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 494 0 09 Feb 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 131 438 0 18 Dec 2020