24 citations · 36 across the 4 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★ 24 cited
Learn molecular representations from large-scale unlabeled molecules for drug discovery
Pengyong Li, Jun Wang, Yixuan Qiao +6
How to produce expressive molecular representations is a fundamental challenge in AI-driven drug discovery. Graph neural network (GNN) has emerged as a powerful technique for model…