On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers

1 code implementation • 4 Apr 2024 • Cai Zhou, Rose Yu, Yusu Wang

In this paper, we provide a systematic study of the theoretical expressive power of order-$k$ graph transformers and sparse variants.

Graph Attention Graph Learning

Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes

1 code implementation • NeurIPS 2023 • Cai Zhou, Xiyuan Wang, Muhan Zhang

Second, on $1$-simplices or edge level, we bridge edge-level random walk and Hodge $1$-Laplacians and design corresponding edge PE respectively.

From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks

1 code implementation • 8 May 2023 • Cai Zhou, Xiyuan Wang, Muhan Zhang

Relational pooling is a framework for building more expressive and permutation-invariant graph neural networks.