A practical PINN framework for multi-scale problems with multi-magnitude loss terms

13 August 2023

Papers citing "A practical PINN framework for multi-scale problems with multi-magnitude loss terms"

5 / 5 papers shown

Title
Improved physics-informed neural network in mitigating gradient related failures Pancheng Niu Yongming Chen Jun Guo Yuqian Zhou Minfu Feng Yanchao Shi PINN AI4CE 26 0 0 28 Jul 2024
Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be? Jorge F. Urbán P. Stefanou José A. Pons PINN 45 6 0 07 May 2024
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 48 210 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 131 439 0 18 Dec 2020
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains Ziqi Liu Wei Cai Zhi-Qin John Xu AI4CE 264 122 0 22 Jul 2020