26 citations · 28 across the 5 of their papers we have counts for
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cs.LG2024★ 1 cited
SGFormer: Single-Layer Graph Transformers with Approximation-Free Linear Complexity
Qitian Wu, Kai Yang, Hengrui Zhang +2
Learning representations on large graphs is a long-standing challenge due to the inter-dependence nature. Transformers recently have shown promising performance on small graphs tha…
cs.LG2024★ 1 cited
Transformers from Diffusion: A Unified Framework for Neural Message Passing
Qitian Wu, David Wipf, Junchi Yan
Learning representations for structured data with certain geometries (e.g., observed or unobserved) is a fundamental challenge, wherein message passing neural networks (MPNNs) have…