Ensemble graph auto-encoders for clustering and link prediction

Graph auto-encoders are a crucial research area within graph neural networks, commonly employed for generating graph embeddings while minimizing errors in unsupervised learning. Traditional graph auto-encoders focus on reconstructing minimal graph data loss to encode neighborhood information for eac...

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Podrobná bibliografie

Hlavní autoři:	Chengxin Xie, Jingui Huang, Yongjiang Shi, Hui Pang, Liting Gao, Xiumei Wen
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	PeerJ Inc. 2025-01-01
Edice:	PeerJ Computer Science
Témata:	Graph auto-encoders Low embedding Ensemble Link prediction Clustering
On-line přístup:	https://peerj.com/articles/cs-2648.pdf
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