64 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
3 papers
Graph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph
Linfeng Cao, Haoran Deng, Yang Yang +2
Due to the ubiquity of graph data on the web, web graph mining has become a hot research spot. Nonetheless, the prevalence of large-scale web graphs in real applications poses sign…
Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks
Jiarong Xu, Renhong Huang, Xin Jiang +4
Pre-training on graph neural networks (GNNs) aims to learn transferable knowledge for downstream tasks with unlabeled data, and it has recently become an active research area. The…
DropMessage: Unifying Random Dropping for Graph Neural Networks
Taoran Fang, Zhiqing Xiao, Chunping Wang +3
Graph Neural Networks (GNNs) are powerful tools for graph representation learning. Despite their rapid development, GNNs also face some challenges, such as over-fitting, over-smoot…