Dual generative adversarial graph networks: Unsupervised and semi-supervised learning with spherical graph embeddings.

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Bibliographic Details
Title: Dual generative adversarial graph networks: Unsupervised and semi-supervised learning with spherical graph embeddings.
Authors: Zhang W; Guangdong Provincial/Zhuhai Key Laboratory IRADS and Department of Computer Science, Beijing Normal-Hong Kong Baptist University, Zhuhai, Guangdong, 519807, China; Hong Kong Baptist University, Kowloon, Hong Kong, 999077, China. Electronic address: t330201704@mail.uic.edu.cn., Fan W; Guangdong Provincial/Zhuhai Key Laboratory IRADS and Department of Computer Science, Beijing Normal-Hong Kong Baptist University, Zhuhai, Guangdong, 519807, China. Electronic address: wentaofan@uic.edu.cn., Chen Y; Department of Computer Science and Technology, Huaqiao University, Xiamen, Fujian, 361021, China. Electronic address: ywchen@hqu.edu.cn.
Source: Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2026 Aug; Vol. 200, pp. 108801. Date of Electronic Publication: 2026 Mar 02.
Publication Type: Comparative Study; Journal Article
Journal Info: Publisher: Pergamon Press Country of Publication: United States NLM ID: 8805018 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2782 (Electronic) Linking ISSN: 08936080 NLM ISO Abbreviation: Neural Netw Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-2782
DOI:10.1016/j.neunet.2026.108801