Optimizing Variational Graph Autoencoder for Community Detection with Dual Optimization

Variational Graph Autoencoder (VGAE) has recently gained traction for learning representations on graphs. Its inception has allowed models to achieve state-of-the-art performance for challenging tasks such as link prediction, rating prediction, and node clustering. However, a fundamental flaw exists...

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Bibliographic Details

Published in:	Entropy (Basel, Switzerland) Vol. 22; no. 2; p. 197
Main Authors:	Choong, Jun Jin, Liu, Xin, Murata, Tsuyoshi
Format:	Journal Article
Language:	English
Published:	MDPI 01.02.2020 MDPI AG
Subjects:	graph neural network network embedding variational autoencoder variational inference
ISSN:	1099-4300, 1099-4300
Online Access:	Get full text
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