103 citations · 179 across the 9 of their papers we have counts for
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cs.LG2021★ 4 cited
DyFormer: A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability
Weilin Cong, Yanhong Wu, Yuandong Tian +4
Transformers have achieved great success in several domains, including Natural Language Processing and Computer Vision. However, its application to real-world graphs is less explor…
cs.LG2018★ 65 cited
Dynamic Graph Representation Learning via Self-Attention Networks
Aravind Sankar, Yanhong Wu, Liang Gou +2
Learning latent representations of nodes in graphs is an important and ubiquitous task with widespread applications such as link prediction, node classification, and graph visualiz…