20 citations · 29 across the 4 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
cs.LG2022★ 20 cited
Uncovering the Structural Fairness in Graph Contrastive Learning
Ruijia Wang, Xiao Wang, Chuan Shi +1
Recent studies show that graph convolutional network (GCN) often performs worse for low-degree nodes, exhibiting the so-called structural unfairness for graphs with long-tailed deg…
cs.LG2022★ 5 cited
Graph Condensation via Receptive Field Distribution Matching
Mengyang Liu, Shanchuan Li, Xinshi Chen +1
Graph neural networks (GNNs) enable the analysis of graphs using deep learning, with promising results in capturing structured information in graphs. This paper focuses on creating…