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Deep convolutional adversarial graph autoencoder using positive pointwise mutual information for graph embedding

MA Xiuhui WANG Rong CHEN Shudong DU Rong ZHU Danyang ZHAO Hua

高技术通讯（英文版）2022，Vol.28Issue(1)：98-106,9.

高技术通讯（英文版）2022，Vol.28Issue(1)：98-106,9.DOI:10.3772/j.issn.1006-6748.2022.01.012

Deep convolutional adversarial graph autoencoder using positive pointwise mutual information for graph embedding

MA Xiuhui ¹WANG Rong ²CHEN Shudong ³DU Rong ¹ZHU Danyang ²ZHAO Hua¹

作者信息

1. University of Chinese Academy of Sciences,Beijing 100049,P.R.China
2. Institute of Microelectronics of the Chinese Academy of Sciences,Beijing 100029,P.R.China
3. Key Laboratory of Space Object Measurement Department,Beijing Institute of Tracking and Telecommunications Technology,Beijing 100094,P.R.China
折叠

摘要

关键词

graph autoencoder ( GAE)/positive pointwise mutual information ( PPMI)/deep convolutional generative adversarial network ( DCGAN)/graph convolutional network ( GCN)/se-mantic information

Key words

graph autoencoder ( GAE)/positive pointwise mutual information ( PPMI)/deep convolutional generative adversarial network ( DCGAN)/graph convolutional network ( GCN)/se-mantic information

引用本文复制引用

MA Xiuhui,WANG Rong,CHEN Shudong,DU Rong,ZHU Danyang,ZHAO Hua..Deep convolutional adversarial graph autoencoder using positive pointwise mutual information for graph embedding[J].高技术通讯（英文版）,2022,28(1):98-106,9.

基金项目

Supported by the Strategy Priority Research Program of Chinese Academy of Sciences(No.XDC02070600). （No.XDC02070600）

高技术通讯（英文版）

OAEI

ISSN：1006-6748

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