Zhonglin Ye

FDAGCL:Feature Discrepancy-Aware Graph Contrastive Learning

2026 · Neural Processing Letters

In recent years, Graph Contrastive Learning (GCL) has emerged as a key research direction for learning representations of unlabeled graph data, focusing on the self-supervised learning of efficient representations for both graphs and nodes. However, …