81 citations · 105 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 23 cited
Graph Random Neural Network for Semi-Supervised Learning on Graphs
Wenzheng Feng, Jie Zhang, Yuxiao Dong +6
We study the problem of semi-supervised learning on graphs, for which graph neural networks (GNNs) have been extensively explored. However, most existing GNNs inherently suffer fro…
cs.SI2018★ 81 cited
Semi-supervised Learning on Graphs with Generative Adversarial Nets
Ming Ding, Jie Tang, Jie Zhang
We investigate how generative adversarial nets (GANs) can help semi-supervised learning on graphs. We first provide insights on working principles of adversarial learning over grap…
cs.SI2018★ 1 cited
Spectral Network Embedding: A Fast and Scalable Method via Sparsity
Jie Zhang, Yan Wang, Jie Tang +1
Network embedding aims to learn low-dimensional representations of nodes in a network, while the network structure and inherent properties are preserved. It has attracted tremendou…