Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Overview

Outlier Exposure

This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019).

Requires Python 3+ and PyTorch 0.4.1+.

Overview

Outlier Exposure (OE) is a method for improving anomaly detection performance in deep learning models. Using an out-of-distribution dataset, we fine-tune a classifier so that the model learns heuristics to distinguish anomalies and in-distribution samples. Crucially, these heuristics generalize to new distributions. Unlike ODIN, OE does not require a model per OOD dataset and does not require tuning on "validation" examples from the OOD dataset in order to work. This repository contains a subset of the calibration and multiclass classification experiments. Please consult the paper for the full results and method descriptions.

Contained within this repository is code for the NLP experiments and the multiclass and calibration experiments for SVHN, CIFAR-10, CIFAR-100, and Tiny ImageNet.

80 Million Tiny Images is available here (mirror link).

Citation

If you find this useful in your research, please consider citing:

@article{hendrycks2019oe,
  title={Deep Anomaly Detection with Outlier Exposure},
  author={Hendrycks, Dan and Mazeika, Mantas and Dietterich, Thomas},
  journal={Proceedings of the International Conference on Learning Representations},
  year={2019}
}

Outlier Datasets

These experiments make use of numerous outlier datasets. Links for less common datasets are as follows, 80 Million Tiny Images (mirror link), Icons-50, Textures, Chars74K, and Places365.

Owner
Dan Hendrycks
PhD student at UC Berkeley.
Dan Hendrycks
Learning based AI for playing multi-round Koi-Koi hanafuda card games. Have fun.

Koi-Koi AI Learning based AI for playing multi-round Koi-Koi hanafuda card games. Platform Python PyTorch PySimpleGUI (for the interface playing vs AI

Sanghai Guan 10 Nov 20, 2022
Baseline for the Spoofing-aware Speaker Verification Challenge 2022

Introduction This repository contains several materials that supplements the Spoofing-Aware Speaker Verification (SASV) Challenge 2022 including: calc

40 Dec 28, 2022
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.

PEPit: Performance Estimation in Python This open source Python library provides a generic way to use PEP framework in Python. Performance estimation

Baptiste 53 Nov 16, 2022
Video Matting via Consistency-Regularized Graph Neural Networks

Video Matting via Consistency-Regularized Graph Neural Networks Project Page | Real Data | Paper Installation Our code has been tested on Python 3.7,

41 Dec 26, 2022
Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling".

PSSL Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling". It consists of the pre-tra

2 Dec 21, 2021
Using deep learning model to detect breast cancer.

Breast-Cancer-Detection Breast cancer is the most frequent cancer among women, with around one in every 19 women at risk. The number of cases of breas

1 Feb 13, 2022
Package to compute Mauve, a similarity score between neural text and human text. Install with `pip install mauve-text`.

MAUVE MAUVE is a library built on PyTorch and HuggingFace Transformers to measure the gap between neural text and human text with the eponymous MAUVE

Krishna Pillutla 182 Jan 02, 2023
Application of K-means algorithm on a music dataset after a dimensionality reduction with PCA

PCA for dimensionality reduction combined with Kmeans Goal The Goal of this notebook is to apply a dimensionality reduction on a big dataset in order

Arturo Ghinassi 0 Sep 17, 2022
Simultaneous NMT/MMT framework in PyTorch

This repository includes the codes, the experiment configurations and the scripts to prepare/download data for the Simultaneous Machine Translation wi

<a href=[email protected]"> 37 Sep 29, 2022
Must-read Papers on Physics-Informed Neural Networks.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

IDRL 330 Jan 07, 2023
Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based Analysis Framework"

Privacy-Aware Inverse RL (PRIL) Analysis Framework Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based

1 Dec 06, 2021
Reproducing-BowNet: Learning Representations by Predicting Bags of Visual Words

Reproducing-BowNet Our reproducibility effort based on the 2020 ML Reproducibility Challenge. We are reproducing the results of this CVPR 2020 paper:

6 Mar 16, 2022
An open source object detection toolbox based on PyTorch

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.

Bo Chen 24 Dec 28, 2022
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)

Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei*, Maya Kabkab*, Rama Chellappa [*: authors co

Maya Kabkab 212 Dec 07, 2022
Code for testing convergence rates of Lipschitz learning on graphs

📈 LipschitzLearningRates The code in this repository reproduces the experimental results on convergence rates for k-nearest neighbor graph infinity L

2 Dec 20, 2021
Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"

NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B

Bee Lim 625 Dec 30, 2022
Adversarial vulnerability of powerful near out-of-distribution detection

Adversarial vulnerability of powerful near out-of-distribution detection by Stanislav Fort In this repository we're collecting replications for the ke

Stanislav Fort 9 Aug 30, 2022
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.

OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters

THUNLP 386 Dec 26, 2022
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.

Reinforcement-Learning-Notebooks A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented

Pulkit Khandelwal 1k Dec 28, 2022
[IROS'21] SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning

SurRoL IROS 2021 SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning Features dVRK compati

<a href=[email protected]"> 55 Jan 03, 2023