12 citations · 31 across the 7 of their papers we have counts for
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cs.LG2022
HCL: Improving Graph Representation with Hierarchical Contrastive Learning
Jun Wang, Weixun Li, Changyu Hou +6
Contrastive learning has emerged as a powerful tool for graph representation learning. However, most contrastive learning methods learn features of graphs with fixed coarse-grained…
cs.LG2020★ 12 cited
Learning Graph Normalization for Graph Neural Networks
Yihao Chen, Xin Tang, Xianbiao Qi +2
Graph Neural Networks (GNNs) have attracted considerable attention and have emerged as a new promising paradigm to process graph-structured data. GNNs are usually stacked to multip…