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WentaoZhang

2 accepted papers

2025

STRAP: Spatio-Temporal Pattern Retrieval for Out-of-Distribution Generalization

NeurIPS 2025poster

Spatio-Temporal Graph Neural Networks (STGNNs) have emerged as a powerful tool for modeling dynamic graph-structured data across diverse domains. However, they often fail to generalize in Spatio-Temporal Out-of-Distribution (STOOD) scenarios, where both temporal dynamics and spatial structures evolv…

Cited by 0SourceScholar
2024

RAGraph: A General Retrieval-Augmented Graph Learning Framework

NeurIPS 2024poster

Graph Neural Networks (GNNs) have become essential in interpreting relational data across various domains, yet, they often struggle to generalize to unseen graph data that differs markedly from training instances. In this paper, we introduce a novel framework called General Retrieval-Augmented Graph…