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cs.LG2026
Gaussian Relational Graph Transformer
Zezhong Ding, Jin Li, Xugang Wang +1
Relational graph learning enables predictive modeling over relational databases by directly capturing dependencies across interconnected tables. While relational graph Transformers…
cs.LG2026
Learning Graph Foundation Models on Riemannian Graph-of-Graphs
Haokun Liu, Zezhong Ding, Xike Xie
Graph foundation models (GFMs), pretrained on massive graph data, have transformed graph machine learning by supporting general-purpose reasoning across diverse graph tasks and dom…
cs.LG2025
SamGoG: A Sampling-Based Graph-of-Graphs Framework for Imbalanced Graph Classification
Shangyou Wang, Zezhong Ding, Xike Xie
Graph Neural Networks (GNNs) have shown remarkable success in graph classification tasks by capturing both structural and feature-based representations. However, real-world graphs…