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ad_examples

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.

ai_projects

Artificial Intelligence

alocc-cvpr2018

Adversarially Learned One-Class Classifier for Novelty Detection (ALOCC)

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

awesome-ts-anomaly-detection

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

boruta-shap

A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.

boruta_py

Python implementations of the Boruta all-relevant feature selection method.

caffe_deep_learning_for_steganalysis

cats_vs_dogs

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

comdefend

The code for CVPR2019 (ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples)

constructed-datasets

Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"

da

Unsupervised Domain Adaptation Papers and Code

dann

Unsupervised Domain Adaptation by Backpropagation

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

deep-embedded-validation

Code release for Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation (ICML 2019)

deep-learning-for-anomaly-detection-a-survey

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

deep-learning-on-image-denoising-an-overview

Deep Learning on Image Denoising: An overview (Neural Networks, 2020)

deeplabv3-plus-pytorch

这是一个deeplabv3-plus-pytorch的源码，可以用于训练自己的模型。

deviation-network

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

discriminative-feature-alignment

Discriminative Feature Alignment for Unsupervised Domain Adaptation

dl-uncertainty

"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).

dncnn

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)

domain_adaptation

this project is the code of domain adaptation referenced by unsupervised domain adaptation by backpropagation(http://machinelearning.wustl.edu/mlpapers/paper_files/icml2015_ganin15.pdf).And i realized it on mnist.

dsfs

Unsupervised Feature Selection for Outlier Detection

dudenet

Designing and Training of A Dual CNN for Image Denoising (Knowledge-based Systems, 2021)

ege-unet

This is the official code repository for "EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation".

eql.detectron2

The official implementation of Equalization Loss for Long-Tailed Object Recognition (CVPR 2020) based on Detectron2. https://arxiv.org/abs/2003.05176

error-detection

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

etn

Code released for CVPR 2019 paper "Learning to Transfer Examples for Partial Domain Adaptation"