Explaining anomalies through semi-supervised Autoencoders

This work tackles the problem of designing explainable by design anomaly detectors, which provide intelligible explanations to abnormal behaviors in input data observations. In particular, we adopt heatmaps as explanations, where a heatmap can be regarded as a collection of per-feature scores. To ex...

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Bibliographic Details

Published in:	Array (New York) Vol. 28; p. 100537
Main Authors:	Angiulli, Fabrizio, Fassetti, Fabio, Ferragina, Luca, Nisticò, Simona
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.12.2025
Subjects:	Anomaly detection Explainability by design Explainable Artificial Intelligence Green-aware AI Explainable Artificial Intelligence Green-aware AI Explainability by design Anomaly detection
ISSN:	2590-0056, 2590-0056
Online Access:	Get full text
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