2 papers
cs.LG2026
Retrieval Over Training: Similarity search-based Model Selection for Time Series Anomaly Detection
Christos Panourgias, Roberto Stanzione, Adrien Petralia +2
Anomaly detection is a fundamental task for time-series analytics, with important implications for the downstream performance of many applications. Despite the large number of anom…
cs.LG2026
Detect, Explain, Interpret: An End-to-End Benchmark for Time Series Anomaly Detection, Explainability and Interpretability
Roberto Stanzione, Jules Barbe, Magali Parrino +2
Time Series Anomaly Detection has received increasing attention, driven by the growing availability of complex time series data. This surge has led to the development of numerous d…