3 papers
cs.LG2023
Prioritized Propagation in Graph Neural Networks
Yao Cheng, Minjie Chen, Xiang Li +2
Graph neural networks (GNNs) have recently received significant attention. Learning node-wise message propagation in GNNs aims to set personalized propagation steps for different n…
cs.LG2023
DropMix: Better Graph Contrastive Learning with Harder Negative Samples
Yueqi Ma, Minjie Chen, Xiang Li
While generating better negative samples for contrastive learning has been widely studied in the areas of CV and NLP, very few work has focused on graph-structured data. Recently,…
cs.LG2023
Graph Self-Contrast Representation Learning
Minjie Chen, Yao Cheng, Ye Wang +2
Graph contrastive learning (GCL) has recently emerged as a promising approach for graph representation learning. Some existing methods adopt the 1-vs-K scheme to construct one posi…