Binary structured physics-informed neural networks for solving equations with rapidly changing solutions

23 January 2024

Papers citing "Binary structured physics-informed neural networks for solving equations with rapidly changing solutions"

7 / 7 papers shown

Title
Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study J. Abbasi Ameya D. Jagtap Ben Moseley Aksel Hiorth P. Andersen PINN AI4CE 46 1 0 14 Mar 2025
An explainable operator approximation framework under the guideline of Green's function Jianghang Gu Ling Wen Yuntian Chen Shiyi Chen 71 0 0 21 Dec 2024
Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems Paul Escapil-Inchauspé G. A. Ruz 32 32 0 13 May 2022
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 58 60 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 45 209 0 16 Jul 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
Equalization Loss for Long-Tailed Object Recognition Jingru Tan Changbao Wang Buyu Li Quanquan Li Wanli Ouyang Changqing Yin Junjie Yan 257 457 0 11 Mar 2020