A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

A python library for user-friendly forecasting and anomaly detection on time series.

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

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

Anomaly Detection with R

Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。

List of tools & datasets for anomaly detection on time-series data.

A curated list of awesome anomaly detection resources

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

Find big moving stocks before they move using machine learning and anomaly detection

A curated list of Graph/Transformer-based fraud, anomaly, and outlier detection papers & resources

A Python Library for Graph Outlier Detection (Anomaly Detection)

A machine learning toolkit for log-based anomaly detection [ISSRE'16]

Unsupervised time series anomaly detection library

RNN based Time-series Anomaly detector model implemented in Pytorch.

Anomaly Detection and Correlation library

A Python toolkit for rule-based/unsupervised anomaly detection in time series

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

About Code release for "Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy" (ICLR 2022 Spotlight), https://openreview.net/forum?id=LzQQ89U1qm_

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana

KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps

A PyTorch implementation of the Deep SVDD anomaly detection method

Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.