260 citations · 333 across the 15 of their papers we have counts for
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cs.LG2022★ 38 cited
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng +4
We investigate graph neural networks on graphs with heterophily. Some existing methods amplify a node's neighborhood with multi-hop neighbors to include more nodes with homophily.…
cs.LG2022★ 4 cited
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning
Di Jin, Luzhi Wang, Yizhen Zheng +4
Graph similarity learning refers to calculating the similarity score between two graphs, which is required in many realistic applications, such as visual tracking, graph classifica…
cs.IR2022
WSLRec: Weakly Supervised Learning for Neural Sequential Recommendation Models
Jingwei Zhuo, Bin Liu, Xiang Li +2
Learning the user-item relevance hidden in implicit feedback data plays an important role in modern recommender systems. Neural sequential recommendation models, which formulates l…