PageRank Centrality based Graph Convolutional Networks for Semi-supervised Node Classification

Graph convolutional neural networks(GCNs) have achieved impressive results on a variety of graph-based tasks. However, due to the problem of over-smoothing, the output representation of each node in the graph converges to the same asymptotically with increasing depth of GCN, so the vast majority of GCN models in practical applications are shallow. In this paper, we investigate deep GCNs and propos...