DHI/tsod

Evaluation Tool for Anomaly Detection Algorithms on Time Series

Temporal online machines: streaming anomaly detection with calibrated p-values, built on skaters

Time-Series Anomaly Detection | Algorithms + Datasets + Tutorials

Unsupervised time series anomaly detection library

Real-time anomaly detection for time series metrics. 11 years of production anomaly detection evolution. Multi-algorithm ensembles. Pattern recognition using semi-supervised and unsupervised learning. Correlation analysis. Learns and gets better over time. No GPU required, can run on a VPS.

MOMENT: A Family of Open Time-series Foundation Models, ICML'24

A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

Merlion: A Machine Learning Framework for Time Series Intelligence

Streaming anomaly detection in Python: 16 online detectors (xStream, LODA, RS-Hash, Half-Space Trees, RRCF…) plus calibration and prequential evaluation for real-time data.