2020

Simple and Deep Graph Convolutional Networks

Chen, Ming, Wei, Zhewei, Huang, Zengfeng et al.

Understand

Graph convolutional networks (GCNs) are a powerful deep learning approach for graph-structured data.

Recently, GCNs and subsequent variants have shown superior performance in various application areas on real-world datasets.
Despite their success, most of the current GCN models are shallow, due to the {\em over-smoothing} problem.
In this paper, we study the problem of designing and analyzing deep graph convolutional networks.

Built on

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