Dual Space Graph Contrastive Learning. (arXiv:2201.07409v1 [cs.LG])

Unsupervised graph representation learning has emerged as a powerful tool to
address real-world problems and achieves huge success in the graph learning
domain. Graph contrastive learning is one of the unsupervised graph
representation learning methods, which recently attracts attention from
researchers and has achieved state-of-the-art performances on various tasks.
The key to the success of graph contrastive learning is to construct proper
contrasting pairs to acquire the underlying structural semantics of the graph.
However, this key part is not fully …

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