Anomaly detection related books, papers, videos, and toolboxes
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Updated
Jul 11, 2024 - Python
Anomaly detection related books, papers, videos, and toolboxes
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
List of tools & datasets for anomaly detection on time-series data.
🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps
ELKI Data Mining Toolkit
A curated list of graph-based fraud, anomaly, and outlier detection papers & resources
TODS: An Automated Time-series Outlier Detection System
A Deep Graph-based Toolbox for Fraud Detection
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.
A Python Library for Graph Outlier Detection (Anomaly Detection)
Benchmarking Generalized Out-of-Distribution Detection
A python library for time-series smoothing and outlier detection in a vectorized way.
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.
Luminaire is a python package that provides ML driven solutions for monitoring time series data.
GAAL-based Outlier Detection
ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.
SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.
Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection, semi-supervised anomaly detection
Anomaly detection for streaming time series, featuring automated model selection.
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