237 Open source projects that are alternatives of or similar to T Bear

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

This repository is the PyTorch implementation of GAN Ensemble for Anomaly Detection.

Anomaly detection implemented in Keras

A Deep Graph-based Toolbox for Fraud Detection

Matlab toolbox for univariate and multivariate analysis of EEG data in the time and frequency domains

An Integrated Experimental Platform for time series data anomaly detection.

Fusion ICA Toolbox (MATLAB)

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

High-performance time series algorithms for Ruby

Anomaly detection

Outdated, see new https://github.com/braindecode/braindecode

ADRepository: Real-world anomaly detection datasets

Anomaly detection related books, papers, videos, and toolboxes

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

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.

Merlion: A Machine Learning Framework for Time Series Intelligence

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

SyntheticSun is a defense-in-depth security automation and monitoring framework which utilizes threat intelligence, machine learning, managed AWS security services and, serverless technologies to continuously prevent, detect and respond to threats.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Unsupervised Anomaly Detection with Generative Adversarial Networks on MIAS dataset

A PyTorch implementation of the Deep SVDD anomaly detection method

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

The MATLAB toolbox for MEG, EEG and iEEG analysis

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

A Python Toolbox for Statistics and Neurophysiological Signal Processing (EEG, EDA, ECG, EMG...).

Python module for hyperspectral image processing

Interactive Brain Playground - Browser based tutorials on EEG with webbluetooth and muse

WinDBG Anti-RootKit Extension

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

Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

Tidy anomaly detection

RNN based Time-series Anomaly detector model implemented in Pytorch.

Contains the thorough experiments made for a FloydHub article on Anomaly Detection

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Thio - a playground for real-time anomaly detection

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)

Blackrock Microsystems Cerebus Link for Neural Signal Processing

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

A thesis submitted for the degree of Master of Science in Computer Networks and Security

A log analysis toolkit for automated anomaly detection [ISSRE'16]

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

Luminaire is a python package that provides ML driven solutions for monitoring time series data.

Useful Toolbox for Anomaly Detection

A large collection of system log datasets for AI-powered log analytics

Faster and more precisely than Grad-CAM

Official implementation of Paper Future Frame Prediction for Anomaly Detection -- A New Baseline, CVPR 2018

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).

A toolkit for automated log parsing [ICSE'19, TDSC'18, DSN'16]

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

An open-source, low-code machine learning library in Python

MNELAB – a GUI for MNE

A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

Hastic data management server for analyzing patterns and anomalies from Grafana

An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana

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.

A Python toolkit for rule-based/unsupervised anomaly detection in time series

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams