Machine learning and domain decomposition methods -- a survey

21 December 2023

Papers citing "Machine learning and domain decomposition methods -- a survey"

7 / 7 papers shown

Title
Multi-Level GNN Preconditioner for Solving Large Scale Problems Matthieu Nastorg J. Gratien T. Faney M. Bucci Guillaume Charpiat Marc Schoenauer AI4CE 19 1 0 13 Feb 2024
Domain decomposition-based coupling of physics-informed neural networks via the Schwarz alternating method Will Snyder Irina Tezaur Christopher Wentland 24 4 0 01 Nov 2023
Learning Interface Conditions in Domain Decomposition Solvers Ali Taghibakhshi Nicolas Nytko Tareq Uz Zaman S. MacLachlan Luke N. Olson Matthew West AI4CE 38 11 0 19 May 2022
Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion S. Basir Inanc Senocak PINN AI4CE 34 68 0 30 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
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on Unseen Domains Hengjie Wang R. Planas Aparna Chandramowlishwaran Ramin Bostanabad AI4CE 47 61 0 22 Apr 2021
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 125 508 0 11 Mar 2020