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cs.LG2026
Rethinking Generalization in Graph Neural Networks: A Structural Complexity Perspective
Peiyao Wang, Liang Bai, Xian Yang +2
Graph neural networks (GNNs) have emerged as a fundamental tool for learning from graph-structured data, achieving strong performance across a wide range of applications. However,…
cs.LG2026
Time-varying Interaction Graph ODE for Dynamic Graph Representation Learning
Xiaoyi Wang, Zhiqiang Wang, Jianqing Liang +4
Graph neural Ordinary Differential Equations (ODE) combine neural ODE with the message passing mechanism of Graph Neural Networks (GNN), providing a continuous-time modeling method…