Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering Dongxiao He
–Neural Information Processing Systems
Graph Contrastive Learning (GCL) has emerged as a powerful approach for generating graph representations without the need for manual annotation. Most advanced GCL methods fall into three main frameworks: node discrimination, group discrimination, and bootstrapping schemes, all of which achieve comparable performance. However, the underlying mechanisms and factors that contribute to their effectiveness are not yet fully understood.
Neural Information Processing Systems
Feb-18-2026, 06:02:21 GMT
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