Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning

no code implementations • 1 Oct 2022 • Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang

The effectiveness is further guaranteed and proved by the gradients' distance between the subset and the full set; (ii) empirically, we discover that during the learning process of a GNN, some samples in the training dataset are informative for providing gradients to update model parameters.

Contrastive Learning Graph Representation Learning

Graph Contrastive Learning with Cross-view Reconstruction

no code implementations • 16 Sep 2022 • Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

In light of this, we introduce the Graph Contrastive Learning with Cross-View Reconstruction (GraphCV), which follows the information bottleneck principle to learn minimal yet sufficient representation from graph data.

Contrastive Learning Disentanglement +3