Enhanced Graph Autoencoder for Graph Anomaly Detection Using Subgraph Information

Graph anomaly detection aims at identifying rare, unusual entities in attributed networks with respect to their patterns or structures that deviate significantly from the majority within a graph. Over the years, extensive efforts in this field have been dedicated to the powerful capability of attrib...

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Bibliographic Details

Published in:	Applied sciences Vol. 15; no. 15; p. 8691
Main Authors:	Zhang, Chi, Jung, Jin-Woo
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2025
Subjects:	Analysis Datasets Deep learning Design Detectors Euclidean space graph anomaly detection graph autoencoders graph neural networks graph structure learning Neighborhoods Neural networks Social network analysis Social networks
ISSN:	2076-3417, 2076-3417
Online Access:	Get full text
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