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DeepOD

Deep learning-based outlier/anomaly detection

outlier-interpretation

(WWW'21) ATON - an Outlier Interpreation / Outlier explanation method

deep-iforest

offical implementation of TKDE paper "Deep isolation forest for anomaly detection"

couta

a time series anomaly detection method based on the calibrated one-class classifier

MIX

ICDM19 - Anomaly Detection / Outlier Detection for Mixed data

EMAC_SCAN

Outlier detection algorithm for categorical data

rosas

official implementation of RoSAS: Deep Semi-supervised Anomaly Detection with Contamination-resilient Continuous Supervision

scale-learning

Deep anomaly detection with scale learning

SelectVC-POP

The source code of POP to detect outliers in high-dimensional categorical data published in CIKM17.

TS-AD-Datasets

Public datasets for time series anomaly detection

WOD

The source code of outlier detection method WOD for categorical data published in DEXA18.

ADRepository-Anomaly-detection-datasets

Anomaly-Detection

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

FLAD

plsd

weakly-supervised anomaly detection

A-Comparative-Study-on-Unsupervised-Anomaly-Detection-forTime-Series

A Comparative Study on Unsupervised Anomaly Detection forTime Series

ADTS

A-Comparative-Study-on-Unsupervised-Anomaly-Detection-forTime-Series

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

Awesome-Meta-Learning

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

awesome-TS-anomaly-detection

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

CCNet

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

dcbrain

dcbrain

FMMS

Factorization Machines based Unsupervised Model Selection Method

HAI-dataset

HIL-based Augmented ICS (HAI) Security Dataset

matrixprofile-ts

A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile

ML-NLP

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

pyod

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

RCA

Implementation for paper: RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection

TensorFlow-Examples

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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