Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
Han Gao,M. Zahr,Jian-Xun Wang
2021 · DOI: 10.1016/j.cma.2021.114502
Computer Methods in Applied Mechanics and Engineering · 241회 인용
TLDR
A novel discrete PINN framework based on graph convolutional network (GCN) and variational structure of PDE to solve forward and inverse partial differential equations (PDEs) in a unified manner and the use of a piecewise polynomial basis can reduce the dimension of search space and facilitate training and convergence.