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Active-Learning

Official Matlab demo for AIFT - CVPR 2017

Anomaly-Detection

Unsupervised / Semisupervised Anomaly Detection

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

awesome-AIOps

AIOps学习资料汇总，欢迎一起补全这个仓库，欢迎star

awesome-log-analysis

A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps

Class-Imbalance-1

Cost-Sensitive Learning / Resampling / SMOTE etc.

ConAD

Implementation of Consistency-based anomaly detection (ConAD)

ConAD-PyTorch

Implementation of Consistency-based anomaly detection (ConAD)

CPIP-1

data-augmentation-review

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.

DeepLog

Pytorch implementation of DeepLog.

df

The source code and dataset are used to demonstrate the DF model, and reproduce the results of the ACM CCS2018 paper

dwmil

Dynamic Weighted Majority for Imbalance Learning

Explaining-DL

FARE

FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data

FEAD

FEAD: Feature Explainable Network Traffic Anomaly Detection Model Based on Fast CNN

ganhacks

starter from "How to Train a GAN?" at NIPS2016

GCN_ADV_Train

Adversarial training for Graph Neural Networks

ise_web

LDAM-DRW

[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

loglizer

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

MACGAN

Realization of paper: "MACGAN : Bypass Traffic Anomaly Detector and Maintain Attack Characteristics"

openwf

self-paced-ensemble

A general & effective ensemble framework for imbalance classification.

SGM-CNN

Our implementations of the flow-based network intrusion detection model (for the COMNET paper)

st-gcn

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

STRAD

TM_prediction

tor-browser-crawler

A crawler based on Tor Browser and Selenium

transferlearning

Everything about Transfer Learning and Domain Adaptation--迁移学习