PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network. - Longxiang Jiang; Liyuan Wang; Xinkun Chu; Yonghao Xiao; Hao Zhang (CACML, 2023)

Combining physics-informed graph neural network and finite difference for solving forward and inverse spatiotemporal PDEs. - Hao Zhang; Longxiang Jiang; Xinkun Chu; Yong Wen; Luxiong Li; Yonghao Xiao; Liyuan Wang (CoRR, 2024)

Combining physics-informed graph neural network and finite difference for solving forward and inverse spatiotemporal PDEs. - Hao Zhang; Longxiang Jiang; Xinkun Chu; Yong Wen; Luxiong Li; Jianbo Liu; Yonghao Xiao; Liyuan Wang (Comput. Phys. Commun., 2025)