3 papers
stat.ML2026
ProtoX-AD: Self-Explainable Time Series Anomaly Detection and Characterization
Aitor Sánchez-Ferrera, Elisabeth Wetzer, Kristoffer Wickstrøm +2
Recent advances in time series anomaly detection (TSAD) have highlighted the effectiveness of self-supervised classification-based approaches. These methods apply transformations t…
cs.LG2025
NeuCoReClass AD: Redefining Self-Supervised Time Series Anomaly Detection
Aitor Sánchez-Ferrera, Usue Mori, Borja Calvo +1
Time series anomaly detection plays a critical role in a wide range of real-world applications. Among unsupervised approaches, self-supervised learning has gained traction for mode…
stat.ML2025
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open Challenges
Aitor Sánchez-Ferrera, Borja Calvo, Jose A. Lozano
Time series anomaly detection presents various challenges due to the sequential and dynamic nature of time-dependent data. Traditional unsupervised methods frequently encounter dif…