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Jiayue Zhou

2 accepted papers

2024

Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention

NeurIPS 2024spotlight

In the realm of graph learning, there is a category of methods that conceptualize graphs as hierarchical structures, utilizing node clustering to capture broader structural information. While generally effective, these methods often rely on a fixed graph coarsening routine, leading to overly homogen…

2023

Tailoring Self-Attention for Graph via Rooted Subtrees

NeurIPS 2023poster

Attention mechanisms have made significant strides in graph learning, yet they still exhibit notable limitations: local attention faces challenges in capturing long-range information due to the inherent problems of the message-passing scheme, while global attention cannot reflect the hierarchical ne…