End-to-End Self-tuning Self-supervised Framework for Versatile Time Series Anomaly Detection

TSAP, a novel self-tuning self-supervised framework, can automatically select the appropriate anomaly type and tune the associated continuous hyperparameters to effectively detect diverse time series anomalies without any labeled data.