30 citations · 36 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks
Shuhao Shi, Jian Chen, Kai Qiao +3
The Graph Convolutional Networks (GCNs) have achieved excellent results in node classification tasks, but the model's performance at low label rates is still unsatisfactory. Previo…
cs.LG2021★ 5 cited
Adaptive Multi-layer Contrastive Graph Neural Networks
Shuhao Shi, Pengfei Xie, Xu Luo +4
We present Adaptive Multi-layer Contrastive Graph Neural Networks (AMC-GNN), a self-supervised learning framework for Graph Neural Network, which learns feature representations of…
cs.LG2021★ 30 cited
Boosting-GNN: Boosting Algorithm for Graph Networks on Imbalanced Node Classification
S. Shi, Kai Qiao, Shuai Yang +3
The Graph Neural Network (GNN) has been widely used for graph data representation. However, the existing researches only consider the ideal balanced dataset, and the imbalanced dat…