Xiaolin Tian

Deep Graph-Convolutional Generative Adversarial Network for Semi-Supervised Learning on Graphs

Nan Jia, Xiaolin Tian, Wenxing Gao, Licheng Jiao

Graph convolutional networks (GCNs) are neural network frameworks for machine learning on graphs. They can simultaneously perform end-to-end learning on the attribute information and the structure information of graph data. However, most existing GCNs inevitably encounter the lim…Read more