168 Open source projects that are alternatives of or similar to outliertree

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

A scikit-learn compatible library for anomaly detection

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

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

Anomaly detection related books, papers, videos, and toolboxes

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

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

TOD: GPU-accelerated Outlier Detection via Tensor Operations

ADRepository: Real-world anomaly detection datasets

Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.

Main component extraction for outlier detection

Code for reproducing f-AnoGAN in Pytorch

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

Official source code of "Fast Adaptive RNN Encoder-Decoder for Anomaly Detection in SMD Assembly Machine"

Deploying a Batch Scoring Pipeline for Python Models

The Combined Anomalous Object Segmentation (CAOS) Benchmark

[ti]ny [li]ttle machine learning [tool]box - Machine learning, anomaly detection, one-class classification, and structured output prediction

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

Implementation of feature engineering from Feature engineering strategies for credit card fraud

A Julia package for robust regressions using M-estimators and quantile regressions

Resources for working with time series and sequence data

PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)

Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"

Faster and more precisely than Grad-CAM

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

⭐ An anomaly-based intrusion detection system.

A quick and dirty vehicle speed detector using video + anomaly detection

DDC-Outlier: Preventing medication errors using unsupervised learning

An R package for space-time anomaly detection using scan statistics.

https://events.kaspersky.com/hackathon/

Official codes for CVPR2021 paper "MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection"

A parallel implementation of local outlier factor based on Spark

Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

High-performance time series algorithms for Ruby

Repository for detecting outliers using Grubb's Threshold & Generalized Extreme Studentized Deviate (ESD) Test

benfordslaw is about the frequency distribution of leading digits.

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

Arduino library for identifying outliers with a Hampel filter

Digital Cell Sorter (DCS): single cell RNA-seq analysis toolkit. Documentation:

Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Solve many kinds of least-squares and matrix-recovery problems

Threat Detection & Anomaly Detection rules for popular open-source components

Sherlock is an anomaly detection service built on top of Druid

基于智能计算框架nupic的异常检测restful Api.

Benchmark for DeepLearning anomaly detection

Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]

fast implementation of singular spectrum transformation (change point detection algorithm)

Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

使用极端值理论(Extreme Value Theory)实现阈值动态自动化设置

VisualQC : assistive tool to ease the quality control workflow of neuroimaging data.

Interactive Visualization to Build, Train and Test an Autoencoder with Tensorflow.js

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

anomaly detection by one-class SVM

anomaly detection with anomalize and Google Trends data

Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo.

No description or website provided.

OpenSnitch is a GNU/Linux application firewall

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning