3 papers
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…
cs.LG2024
GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning
Jianqing Liang, Xinkai Wei, Min Chen +2
Graph contrastive learning (GCL) has become a hot topic in the field of graph representation learning. In contrast to traditional supervised learning relying on a large number of l…
cs.LG2024
Graph External Attention Enhanced Transformer
Jianqing Liang, Min Chen, Jiye Liang
The Transformer architecture has recently gained considerable attention in the field of graph representation learning, as it naturally overcomes several limitations of Graph Neural…