Enhancing training of physics-informed neural networks using
domain-decomposition based preconditioning strategies

Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies

30 June 2023

Alena Kopanicáková

George Karniadakis

Papers citing "Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies"

14 / 14 papers shown

Title
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations Shu Liu Stanley Osher Wuchen Li 26 0 0 09 Nov 2024
Learning a Neural Solver for Parametric PDE to Enhance Physics-Informed Methods Lise Le Boudec Emmanuel de Bezenac Louis Serrano Ramon Daniel Regueiro-Espino Yuan Yin Patrick Gallinari AI4CE 30 2 0 09 Oct 2024
A Nonoverlapping Domain Decomposition Method for Extreme Learning Machines: Elliptic Problems Chang-Ock Lee Youngkyu Lee Byungeun Ryoo 36 3 0 22 Jun 2024
Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications Youngkyu Lee Alena Kopanicáková George Karniadakis AI4CE 33 0 0 16 Jun 2024
Initialization-enhanced Physics-Informed Neural Network with Domain Decomposition (IDPINN) Chenhao Si Ming Yan AI4CE PINN 33 3 0 05 Jun 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 30 6 0 07 May 2024
Learning in PINNs: Phase transition, total diffusion, and generalization Sokratis J. Anagnostopoulos Juan Diego Toscano Nikolaos Stergiopulos George Karniadakis 24 10 0 27 Mar 2024
Machine learning and domain decomposition methods -- a survey A. Klawonn M. Lanser J. Weber AI4CE 16 7 0 21 Dec 2023
Parallel Trust-Region Approaches in Neural Network Training: Beyond Traditional Methods Ken Trotti Samuel A. Cruz Alegría Alena Kopanicáková Rolf Krause 16 0 0 21 Dec 2023
An operator preconditioning perspective on training in physics-informed machine learning Tim De Ryck Florent Bonnet Siddhartha Mishra Emmanuel de Bezenac AI4CE 39 14 0 09 Oct 2023
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 37 207 0 16 Jul 2021
Globally Convergent Multilevel Training of Deep Residual Networks Alena Kopanicáková Rolf Krause 22 15 0 15 Jul 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 98 272 0 20 Apr 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 489 0 09 Feb 2021