#anomaly-detection (30 Repositories)
Ranked open-source repositories tagged with #anomaly-detection, scored by pull request acceptance likelihood and maintainer engagement velocity.
21.6%
122.6h
30 repositories tagged #anomaly-detection
goruck/home-generative-agent
AI agent for Home Assistant — talk to your home, create automations in plain language, analyze cameras with face recognition, and get proactive anomaly alerts. Cloud LLMs or fully local via Ollama.
stumpy-dev/stumpy
STUMPY is a powerful and scalable Python library for modern time series analysis
yzhao062/pyod
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.
RubixML/ML
A high-level machine learning and deep learning library for the PHP language.
open-edge-platform/anomalib
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
unit8co/darts
A python library for user-friendly forecasting and anomaly detection on time series.
selimfirat/pysad
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.
helixmap/sigwood
Local-first, transparent threat hunting for the logs you already have: Zeek, Pi-hole, syslog, CloudTrail. Named technique behind every finding. No SIEM, no agent, no black box.
linkedin/isolation-forest
A distributed Spark/Scala implementation of the isolation forest and extended isolation forest algorithms for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.
kkirchheim/pytorch-ood
👽 Out-of-Distribution Detection with PyTorch
adaptive-machine-learning/CapyMOA
CapyMOA does efficient machine learning for data streams in Python. CapyMOA is a toolbox of methods and evaluators for: classification, regression, clustering, anomaly detection, semi-supervised learning, online continual learning, and drift detection for data streams.
earthgecko/skyline
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.
hoya012/awesome-anomaly-detection
A curated list of awesome anomaly detection resources
hastic-zzz/hastic-server
Hastic data management server for analyzing patterns and anomalies from Grafana
xiahaifeng1995/PaDiM-Anomaly-Detection-Localization-master
This is an unofficial implementation of the paper “PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization”.
ankane/prophet-ruby
Time series forecasting for Ruby
mims-harvard/UniTS
A unified multi-task time series model.
TimyadNyda/Variational-Lstm-Autoencoder
Lstm variational auto-encoder for time series anomaly detection and features extraction
tianyu0207/RTFM
Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]
business-science/anomalize
Tidy anomaly detection
pygod-team/pygod
A Python Library for Graph Outlier Detection (Anomaly Detection)
titicaca/spark-iforest
Isolation Forest on Spark
pycaret/pycaret
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
tradytics/surpriver
Find big moving stocks before they move using machine learning and anomaly detection
activecm/rita
Real Intelligence Threat Analytics (RITA) is a framework for detecting command and control communication through network traffic analysis.
logpai/logparser
A machine learning toolkit for log parsing [ICSE'19, DSN'16]
yzhao062/anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!
isLinXu/paper-list
autoupdate paper list
moment-timeseries-foundation-model/moment
MOMENT: A Family of Open Time-series Foundation Models, ICML'24
Stream-AD/MIDAS
Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.