Weighted dynamic network link prediction based on graph autoencoder

With the development of deep learning, Graph Autoencoders (GAE) within unsupervised learning frameworks have been widely applied to representation learning in dynamic networks. However, existing methods typically assume that the node set remains fixed across all time slices and ignore edge weight in...

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Bibliographic Details

Published in:	Information sciences Vol. 720; p. 122507
Main Authors:	Mei, Peng, Zhao, Yuhong, Wang, Jingyu, Liang, Yefei
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.12.2025
Subjects:	Dynamic network Graph attention Graph autoencoder Link prediction Unsupervised learning Link prediction Graph autoencoder Dynamic network Graph attention Unsupervised learning
ISSN:	0020-0255
Online Access:	Get full text
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