Deep graph level anomaly detection with contrastive learning

Graph level anomaly detection (GLAD) aims to spot anomalous graphs that structure pattern and feature information are different from most normal graphs in a graph set, which is rarely studied by other researchers but has significant application value. For instance, GLAD can be used to distinguish so...

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Detalles Bibliográficos
Autores principales: Luo, Xuexiong, Wu, Jia, Yang, Jian, Xue, Shan, Peng, Hao, Zhou, Chuan, Chen, Hongyang, Li, Zhao, Sheng, Quan Z.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674681/
https://www.ncbi.nlm.nih.gov/pubmed/36400802
http://dx.doi.org/10.1038/s41598-022-22086-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674681/
https://www.ncbi.nlm.nih.gov/pubmed/36400802
http://dx.doi.org/10.1038/s41598-022-22086-3

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