Seeking False Hard Negatives for Graph Contrastive Learning
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DOI: 10.1109/tcsvt.2024.3370149
Abstract: Graph Contrastive Learning (GCL) has achieved great success in self-supervised representation learning throughout positive and negative pairs based on graph neural networks (GNNs), where one critical issue lies in how to handle the false hard… read more here.
Keywords: graph contrastive; contrastive learning; order; hard negatives ... See more keywords