Graph contrastive learning with node-level accurate difference

Graph contrastive learning (GCL) has attracted extensive research interest due to its powerful ability to capture latent structural and semantic information of graphs in a self-supervised manner. Existing GCL methods commonly adopt predefined graph augmentations to generate two contrastive views. Su...

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Bibliographic Details
Main Authors: Pengfei Jiao, Kaiyan Yu, Qing Bao, Ying Jiang, Xuan Guo, Zhidong Zhao
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2025-03-01
Series:Fundamental Research
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2667325824003455
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