458 citations · 467 across the 3 of their papers we have counts for
3 papers
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…
stat.ML2018★ 6 cited
Model Interpretation: A Unified Derivative-based Framework for Nonparametric Regression and Supervised Machine Learning
Xiaoyu Liu, Jie Chen, Joel Vaughan +2
Interpreting a nonparametric regression model with many predictors is known to be a challenging problem. There has been renewed interest in this topic due to the extensive use of m…
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…