64 citations · 78 across the 8 of their papers we have counts for
4 papers · 1 filter
Entropy Neural Estimation for Graph Contrastive Learning
Yixuan Ma, Xiaolin Zhang, Peng Zhang +1
Contrastive learning on graphs aims at extracting distinguishable high-level representations of nodes. In this paper, we theoretically illustrate that the entropy of a dataset can…
GIPA: A General Information Propagation Algorithm for Graph Learning
Houyi Li, Zhihong Chen, Zhao Li +3
Graph neural networks (GNNs) have been widely used in graph-structured data computation, showing promising performance in various applications such as node classification, link pre…
GIPA: General Information Propagation Algorithm for Graph Learning
Qinkai Zheng, Houyi Li, Peng Zhang +4
Graph neural networks (GNNs) have been popularly used in analyzing graph-structured data, showing promising results in various applications such as node classification, link predic…
GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy
Yongchao Liu, Houyi Li, Guowei Zhang +8
Graph neural networks (GNNs) have been demonstrated as a powerful tool for analyzing non-Euclidean graph data. However, the lack of efficient distributed graph learning systems sev…