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143 search results found

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

Darts ⭐ 6,903

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

Awesome Anomaly Detection ⭐ 2,146

A curated list of awesome anomaly detection resources

A high-level machine learning and deep learning library for the PHP language.

Flow Forecast ⭐ 1,759

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

Ailia Models ⭐ 1,708

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

Time Series Transformers Review ⭐ 1,519

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Graph Fraud Detection Papers ⭐ 1,148

A curated list of graph-based fraud, anomaly, and outlier detection papers & resources

Repo 2017 ⭐ 1,146

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Pygod ⭐ 1,138

A Python Library for Graph Outlier Detection (Anomaly Detection)

Training_extensions ⭐ 1,119

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

A machine learning library for detecting anomalies in signals.

Getting Things Done With Pytorch ⭐ 873

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 BERT.

Telemanom ⭐ 793

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

Awesome Aiops ⭐ 747

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

Chaos_genius ⭐ 671

ML powered analytics engine for outlier detection and root cause analysis.

Awesome Industrial Anomaly Detection ⭐ 670

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)。

Awesome Ai For Time Series Papers ⭐ 627

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

Time Series Works Conferences ⭐ 623

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

Adbench ⭐ 609

Official Implement of "ADBench: Anomaly Detection Benchmark".

Handson Unsupervised Learning ⭐ 604

Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)

Awesome Timeseries Spatiotemporal Lm Llm ⭐ 541

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

Deep Svdd Pytorch ⭐ 538

A PyTorch implementation of the Deep SVDD anomaly detection method

Anomaly Transformer ⭐ 471

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

Awesome Anomaly Detection ⭐ 411

A complete list of papers on anomaly detection.

Outlier Exposure ⭐ 378

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Awesome Video Anomaly Detection ⭐ 330

Papers for Video Anomaly Detection, released codes collection, Performance Comparision.

2018 Machinelearning Lectures Esa ⭐ 324

Machine Learning Lectures at the European Space Agency (ESA) in 2018

Deeplog ⭐ 320

Pytorch Implementation of DeepLog.

Credit Card Fraud Detection Using Autoencoders In Keras ⭐ 289

iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

Deepadots ⭐ 270

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

Deep Sad Pytorch ⭐ 268

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

Mtad Gat Pytorch ⭐ 265

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

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

An End-to-end Outlier Detection System

Pytorch_cpp ⭐ 215

Deep Learning sample programs using PyTorch in C++

Awesome Deep Graph Anomaly Detection ⭐ 215

Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

Repository for the Explainable Deep One-Class Classification paper

Machine Learning ⭐ 196

从零基础开始机器学习之旅

Deep Learning For Hackers ⭐ 196

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)

Lstm_anomaly_thesis ⭐ 191

Anomaly detection for temporal data using LSTMs

Novelty Detection ⭐ 183

Latent space autoregression for novelty detection.

Abnormal_event_detection ⭐ 172

Abnormal Event Detection in Videos using SpatioTemporal AutoEncoder

My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

Pytorch Ood ⭐ 166

👽 Out-of-Distribution Detection with PyTorch

Anomalydetectiontransformations ⭐ 137

A simple and effective method for single-class classification of images

Ind_knn_ad ⭐ 130

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

[ECCV'22 Oral] Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes

Unsupervised_anomaly_detection_brain_mri ⭐ 123

Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

Deep Svdd ⭐ 116

Repository for the Deep One-Class Classification ICML 2018 paper

Humanbehaviorbku ⭐ 116

Abnormal Human Behaviors Detection/ Road Accident Detection From Surveillance Videos/ Real-World Anomaly Detection in Surveillance Videos/ C3D Feature Extraction

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Anomagram ⭐ 96

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

Cyber Security ⭐ 89

Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities

Deep Learning For Anomaly Detection A Survey ⭐ 87

This paper is continuously updated with deep anomaly detection methods and their applications

Timeseries Tutorial Kdd 2022 ⭐ 86

KDD'22 Tutorial: Robust Time Series Analysis and Applications An Industrial Perspective

Quick and Easy Time Series Outlier Detection

Student Teacher Anomaly Detection ⭐ 83

Student–Teacher Anomaly Detection with Discriminative Latent Embeddings

Practicalmachinelearning ⭐ 79

A curated collection of machine learning resources, including notebooks, code, and books, all of which are either free or open-source

Out Of Distribution Detection ⭐ 74

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

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Unsupervised Anomaly Detection With Generative Adversarial Networks ⭐ 74

Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

Gcn_anomalydetection ⭐ 73

Code for Deep Anomaly Detection on Attributed Networks (SDM2019)

Revisiting Reverse Distillation ⭐ 66

(CVPR 2023) Revisiting Reverse Distillation for Anomaly Detection

Deviation Network ⭐ 64

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

[NeurlPS 2023] A Dataset and Benchmark for Pose-agnostic Anomaly Detection. Feel free to explore the brand new anomaly detection setting using our dataset🪀!

Project: Unsupervised Anomaly Segmentation via Deep Feature Reconstruction

Mahalanobisad Pytorch ⭐ 56

PyTorch implementation of "Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection"

Official code for 'Deep One-Class Classification via Interpolated Gaussian Descriptor' [AAAI 2022 Oral]

Official Implementation for the "Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection" paper.

List of datasets and papers in X-ray security images (Computer vision/Machine Learning)

Entropic Out Of Distribution Detection ⭐ 47

Add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.

Ood Detection Using Oecc ⭐ 45

Outlier Exposure with Confidence Control for Out-of-Distribution Detection

Fraud Detection Papers ⭐ 45

Learning Fraud Detection from research papers and industry applications.

OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)

MICCAI 2022 (Early Accepted): Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays

Deviation Network Image ⭐ 43

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.

Anomaly_transformer_pytorch ⭐ 42

PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

Anomalydetectionusingautoencoder ⭐ 42

Anomaly detection using Autoencoder implemented with Keras 2.

Cikm22 Tfad ⭐ 37

Source code of CIKM'22 paper: TFAD: A Decomposition Time Series Anomaly Detection Architecture with Frequency Analysis

Meta Aad ⭐ 37

[ICDM 2020] Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning

Dcase2020_task2_baseline ⭐ 37

DCASE2020 Challenge Task 2 baseline system

Cutpaste ⭐ 36

Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch

Anomaly Event Detection ⭐ 36

Work in progress and needs a lot of changes for now. An implementation of paper Detecting anomalous events in videos by learning deep representations of appearance and motion on python, opencv and tensorflow. This paper uses the stacked denoising autoencoder for the the feature training on the appearance and motion flow features as input for different window size and using multiple SVM as a single classifier this is work under progress.

Ubnormal ⭐ 35

UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection

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

Distinction Maximization Loss ⭐ 34

Improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.

Inspection of Power Line Assets: the Dataset (InsPLAD)

An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted by AAAI 2023.

Weakly Polyp ⭐ 30

[MICCAI'22] Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection.

Ddad Asr ⭐ 30

[MedIA'2023] Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical images

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

Awesome 3d Anomaly Detection ⭐ 30

Awesome-3D/Multimodal-Anomaly-Detection-and-Locali

This is the official repo of paper accepted in AAAI 2023 Oral.

Vae Anomaly Detector ⭐ 29

Experiments on unsupervised anomaly detection using variational autoencoder. The variational autoencoder is implemented in Pytorch.

Package for Time Series Forecasting and Anomaly Detection Problems.

Quadra: Effortless and reproducible deep learning workflows with configuration files.

Mvts Ano Eval ⭐ 26

A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Beginning Anomaly Detection Using Python Based Dl ⭐ 23

Source Code for 'Beginning Anomaly Detection Using Python-Based Deep Learning' by Sridhar Alla and Suman Kalyan Adari

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