12 citations · 36 across the 8 of their papers we have counts for
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cs.LG2023★ 2 cited
Subgraph Networks Based Contrastive Learning
Jinhuan Wang, Jiafei Shao, Zeyu Wang +3
Graph contrastive learning (GCL), as a self-supervised learning method, can solve the problem of annotated data scarcity. It mines explicit features in unannotated graphs to genera…
cs.LG2023★ 1 cited
Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning
Dayuan Chen, Jian Zhang, Yuqian Lv +5
Graph neural networks (GNNs) have achieved remarkable success in various real-world applications. However, recent studies highlight the vulnerability of GNNs to malicious perturbat…