ICML 2024 "graph transformers" Papers
10 papers found
Aligning Transformers with Weisfeiler-Leman
Luis Müller, Christopher Morris
ICML 2024poster
CKGConv: General Graph Convolution with Continuous Kernels
Liheng Ma, Soumyasundar Pal, Yitian Zhang et al.
ICML 2024poster
Comparing Graph Transformers via Positional Encodings
Mitchell Black, Zhengchao Wan, Gal Mishne et al.
ICML 2024poster
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné et al.
ICML 2024poster
Less is More: on the Over-Globalizing Problem in Graph Transformers
Yujie Xing, Xiao Wang, Yibo Li et al.
ICML 2024poster
On the Expressive Power of Spectral Invariant Graph Neural Networks
Bohang Zhang, Lingxiao Zhao, Haggai Maron
ICML 2024poster
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding, Antonio Orvieto, Bobby He et al.
ICML 2024poster
Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products
Guy Bar Shalom, Beatrice Bevilacqua, Haggai Maron
ICML 2024poster
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
Md Shamim Hussain, Mohammed Zaki, Dharmashankar Subramanian
ICML 2024poster
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding
Hongkang Li, Meng Wang, Tengfei Ma et al.
ICML 2024poster