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

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Anomaly detection related books, papers, videos, and toolboxes

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

ADRepository: Real-world anomaly detection datasets

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

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

Main component extraction for outlier detection

TOD: GPU-accelerated Outlier Detection via Tensor Operations

A scikit-learn compatible library for anomaly detection

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

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.

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

(Python, R, C++) Explainable outlier/anomaly detection through decision tree conditioning

Anomaly detection library based on singular spectrum transformation(sst)

The fundamental package for AIops with python.

Unofficial Tensorflow Implementation of AnoGAN (Anomaly GAN)

Pytorch Implementation of DeepLog.

The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks

Go implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

Anomaly detection for temporal data using LSTMs

Log Anomaly Detection - Machine learning to detect abnormal events logs

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

Hastic data management server for labeling patterns and anomalies in Grafana

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

The Kubervisor allow you to control which pods should receive traffic or not based on anomaly detection.It is a new kind of health check system.

Unsupervised anomaly detection with generative model, keras implementation

DDC-Outlier: Preventing medication errors using unsupervised learning

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

Fairness regulator and rate limiter

A Python library for anomaly detection

Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

Arduino library for identifying outliers with a Hampel filter

some anomaly detection models and experiments.

Open-source framework to detect outliers in Elasticsearch events

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

Isolation Forest on Spark

Anomaly detection for streaming time series, featuring automated model selection.

Repository for the Deep One-Class Classification ICML 2018 paper

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

STUMPY is a powerful and scalable Python library for modern time series analysis

An End-to-end Outlier Detection System

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

A parallel implementation of local outlier factor based on Spark

Latent space autoregression for novelty detection.

Python toolbox for transfer learning.

Abnormal Event Detection in Videos using SpatioTemporal AutoEncoder

Real-World Anomaly Detection in Surveillance Videos

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

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

A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.

BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics

No description or website provided.

Log-based Impactful Problem Identification using Machine Learning [FSE'18]

A robust, and flexible open source User & Entity Behavior Analytics (UEBA) framework used for Security Analytics. Developed with luv by Data Scientists & Security Analysts from the Cyber Security Industry. [PRE-ALPHA]

Feature Space Singularity for Out-of-Distribution Detection. (SafeAI 2021)

This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'

A Ground Mobile Robot Perception Dataset, IEEE RA-L & IEEE T-CYB

log anomaly detection toolkit including DeepLog

(MLSys' 21) An Acceleration System for Large-scare Unsupervised Heterogeneous Outlier Detection (Anomaly Detection)