458 citations · 467 across the 3 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2022★ 3 cited
Exploiting Neighbor Effect: Conv-Agnostic GNNs Framework for Graphs with Heterophily
Jie Chen, Shouzhen Chen, Junbin Gao +3
Due to the homophily assumption in graph convolution networks (GNNs), a common consensus in the graph node classification task is that GNNs perform well on homophilic graphs but ma…
cs.LG2018★ 458 cited
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie Chen, Tengfei Ma, Cao Xiao
The graph convolutional networks (GCN) recently proposed by Kipf and Welling are an effective graph model for semi-supervised learning. This model, however, was originally designed…