8 citations · 8 across the 1 of their papers we have counts for
3 papers
cs.LG2022
Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective
Yige Yuan, Bingbing Xu, Huawei Shen +4
Graph contrastive learning (GCL) emerges as the most representative approach for graph representation learning, which leverages the principle of maximizing mutual information (Info…
cs.LG2020★ 8 cited
Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning
Bingbing Xu, Huawei Shen, Qi Cao +2
Graph convolutional networks gain remarkable success in semi-supervised learning on graph structured data. The key to graph-based semisupervised learning is capturing the smoothnes…
cs.SI2019
ANAE: Learning Node Context Representation for Attributed Network Embedding
Keting Cen, Huawei Shen, Jinhua Gao +3
Attributed network embedding aims to learn low-dimensional node representations from both network structure and node attributes. Existing methods can be categorized into two groups…