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

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"

Supplementary material for SDM 19 paper "LSCP: Locally Selective Combination in Parallel Outlier Ensembles"

Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"

Detect EEG artifacts, outliers, or anomalies using supervised machine learning.

Implement of paper "Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures"

Unsupervised ensemble anomaly detection model

Build Agent-Native Organizations where AI agents are integral team members with defined roles, governance, and onboarding processes.