MadryLab / cifar10_challenge
A challenge to explore adversarial robustness of neural networks on CIFAR10.
☆489Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for cifar10_challenge
- A challenge to explore adversarial robustness of neural networks on MNIST.☆733Updated 2 years ago
- TRADES (TRadeoff-inspired Adversarial DEfense via Surrogate-loss minimization)☆518Updated last year
- PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.☆243Updated 4 years ago
- [ICLR 2020] A repository for extremely fast adversarial training using FGSM☆431Updated 3 months ago
- Provable adversarial robustness at ImageNet scale☆366Updated 5 years ago
- RobustBench: a standardized adversarial robustness benchmark [NeurIPS 2021 Benchmarks and Datasets Track]☆665Updated this week
- Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"☆656Updated 5 months ago
- Robust evasion attacks against neural network to find adversarial examples☆796Updated 3 years ago
- Related papers for robust machine learning☆564Updated last year
- PyTorch Implementation of Adversarial Training for Free!☆239Updated 3 years ago
- Implementation of Papers on Adversarial Examples☆387Updated last year
- A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.☆917Updated 9 months ago
- Code for ICML 2019 paper "Simple Black-box Adversarial Attacks"☆195Updated last year
- A Toolbox for Adversarial Robustness Research☆1,305Updated last year
- Countering Adversarial Image using Input Transformations.☆489Updated 3 years ago
- LaTeX source for the paper "On Evaluating Adversarial Robustness"☆253Updated 3 years ago
- This is the reading list mainly on adversarial examples (attacks, defenses, etc.) I try to keep and update regularly.☆221Updated 5 years ago
- Simple pytorch implementation of FGSM and I-FGSM☆273Updated 6 years ago
- Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models (published in ICLR2018)☆231Updated 5 years ago
- Pytorch implementation of convolutional neural network adversarial attack techniques☆350Updated 5 years ago
- ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks☆166Updated 3 years ago
- Empirical tricks for training robust models (ICLR 2021)☆249Updated last year
- A method for training neural networks that are provably robust to adversarial attacks.☆380Updated 2 years ago
- This repository provides simple PyTorch implementations for adversarial training methods on CIFAR-10.☆154Updated 3 years ago
- A curated list of awesome resources for adversarial examples in deep learning☆261Updated 3 years ago
- Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"☆185Updated 4 years ago
- Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"☆144Updated 4 years ago
- A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.☆483Updated last year
- A simple and accurate method to fool deep neural networks☆356Updated 4 years ago
- A curated list of papers on adversarial machine learning (adversarial examples and defense methods).☆212Updated 2 years ago