Alternatives and similar repositories for nips17-adversarial-attack:

Users that are interested in nips17-adversarial-attack are comparing it to the libraries listed below

• ftramer / ensemble-adv-training
  Ensemble Adversarial Training on MNIST
  ☆121Updated 7 years ago
• rwightman / pytorch-nips2017-attack-example
  A PyTorch baseline attack example for the NIPS 2017 adversarial competition
  ☆85Updated 7 years ago
• jsikyoon / adv_attack_capsnet
  Tensorflow Implementation of Adversarial Attack to Capsule Networks
  ☆173Updated 7 years ago
• cihangxie / NIPS2017_adv_challenge_defense
  Mitigating Adversarial Effects Through Randomization
  ☆119Updated 6 years ago
• sangxia / nips-2017-adversarial
  Adversarial Attacks and Defenses of Image Classifiers, NIPS 2017 competition track
  ☆45Updated 7 years ago
• lfz / Guided-Denoise
  The winning submission for NIPS 2017: Defense Against Adversarial Attack of team TSAIL
  ☆232Updated 6 years ago
• zhengliz / natural-adversary
  Generating Natural Adversarial Examples, ICLR 2018
  ☆143Updated 6 years ago
• akshaychawla / Adversarial-Examples-in-PyTorch
  Pytorch code to generate adversarial examples on mnist and ImageNet data.
  ☆116Updated 6 years ago
• gongzhitaao / tensorflow-adversarial
  Crafting adversarial images
  ☆223Updated 6 years ago
• facebookarchive / adversarial_image_defenses
  Countering Adversarial Image using Input Transformations.
  ☆491Updated 3 years ago
• huanzhang12 / ZOO-Attack
  ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks
  ☆167Updated 3 years ago
• ysharma1126 / caad_18
  CAAD 2018 winning submissions
  ☆35Updated 6 years ago
• huanzhang12 / Adversarial_Survey
  Robustness vs Accuracy Survey on ImageNet
  ☆98Updated 3 years ago
• rodgzilla / machine_learning_adversarial_examples
  An implementation of the 'fast gradient sign method' from the paper 'Explaining and Harnessing Adversarial Examples'
  ☆54Updated 7 years ago
• bethgelab / adversarial-vision-challenge
  NIPS Adversarial Vision Challenge
  ☆41Updated 6 years ago
• dongyp13 / Targeted-Adversarial-Attack
  A targeted adversarial attack method, which won the NIPS 2017 targeted adversarial attacks competition
  ☆131Updated 6 years ago
• MadryLab / robust-features-code
  Code for "Robustness May Be at Odds with Accuracy"
  ☆92Updated last year
• toshi-k / kaggle-nips-2017-adversarial-attack
  5th place solution in "NIPS 2017: Non-targeted Adversarial Attack" (with solution in targeted attack and defence)
  ☆10Updated 7 years ago
• snakers4 / msc-2018-final
  ☆66Updated 6 years ago
• labsix / adversarial-logit-pairing-analysis
  Analysis of Adversarial Logit Pairing
  ☆60Updated 6 years ago
• labsix / limited-blackbox-attacks
  Code for "Black-box Adversarial Attacks with Limited Queries and Information" (http://arxiv.org/abs/1804.08598)
  ☆175Updated 3 years ago
• dongyp13 / Non-Targeted-Adversarial-Attacks
  A non-targeted adversarial attack method, which won the first place in NIPS 2017 non-targeted adversarial attacks competition
  ☆244Updated 5 years ago
• RanTaimu / Adversarial-Transformation-Network
  A simple implement of an Adversarial Autoencoding ATN(AAE ATN)
  ☆30Updated 7 years ago
• MadryLab / constructed-datasets
  Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"
  ☆184Updated 4 years ago
• ysharma1126 / EAD_Attack
  EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples
  ☆39Updated 6 years ago
• tianzheng4 / Distributionally-Adversarial-Attack
  AAAI 2019 oral presentation
  ☆50Updated 6 months ago
• xuanqing94 / RobGAN
  Rob-GAN: Generator, Discriminator and Adversarial Attacker
  ☆83Updated 5 years ago
• andrewilyas / ens-adv-train-attack
  Circumventing the defense in "Ensemble Adversarial Training: Attacks and Defenses"
  ☆39Updated 6 years ago
• MadryLab / adversarial_spatial
  Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.
  ☆49Updated 5 years ago
• jeromerony / fast_adversarial
  Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"
  ☆134Updated 4 years ago