Jianxin Ren

Discrete Structure Augmentation for Graph Convolutional Networks

Graph Neural Networks (GNNs) have achieved significant progress in semi-supervised data classification, with an assumption that a complete graph or accurate structure is available. In this paper, a novel GNN architecture, named discrete-structure-augmentation graph convolutional network (DSA-GCN) is