Explainable Sequential Anomaly Detection via Prototypes (EASD)

EASD: Explainable Sequential Anomaly Detection via Prototypes

This project develops a prototype-based framework for explainable sequential anomaly detection. Multiple prototypes represent different normal and abnormal sequence patterns, while contrastive learning and k-means clustering support instance-based explanations.