Multiplex Graph Representation Learning Via Dual Correlation Reduction

Author:

Mo Yujie1ORCID,Chen Yuhuan1,Lei Yajie1ORCID,Peng Liang1ORCID,Shi Xiaoshuang1ORCID,Yuan Changan2ORCID,Zhu Xiaofeng3ORCID

Affiliation:

1. Center for Future Media and School of Computer Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

2. Guangxi Academy of Sciences, Nanning, China

3. University of Electronic Science and Technology of China, Chengdu, Sichuan, China

Funder

National Key Research and Development Program of China

University of Electronic Science and Technology of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Reference69 articles.

1. Graph Structure Estimation Neural Networks

2. Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle

3. HDMI: High-order Deep Multiplex Infomax

4. From canonical correlation analysis to self-supervised graph neural networks;zhang;Proc Int Conf Neural Inf Process,2021

5. Multi-view contrastive graph clustering;pan;Proc Int Conf Neural Inf Process,2021

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