Condensed summary of graph anomaly detection methods and their key strengths and limitations.

Condensed summary of graph anomaly detection methods and their key strengths and limitations.

<p>Condensed summary of graph anomaly detection methods and their key strengths and limitations.</p>

Salvato in:
Dettagli Bibliografici
Autore principale: Hossein Rafieizadeh (22676722) (author)
Altri autori: Hadi Zare (20073000) (author), Mohsen Ghassemi Parsa (22676725) (author), Hocine Cherifi (8177628) (author)
Pubblicazione: 2025
Soggetti:
Cell Biology
Science Policy
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
intrusions across social
reconstructions across views
level contrastive learning
dual contrastive learning
across six benchmarks
div >< p
view discrepancies underutilized
augmented graph views
dcor improves auroc
view discrepancies
level contrast
dual autoencoder
augmented view
specific information
six datasets
reduces auroc
publicly available
preserves fine
physical domains
performing non
maximum gain
leaving cross
identifying threats
financial fraud
existing graph
dcor reconstructs
dcor ),
contrasts reconstructions
attributed networks
attribute patterns
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