Alternatives and similar repositories for Bag-of-Tricks-for-AT

Users that are interested in Bag-of-Tricks-for-AT are comparing it to the libraries listed below

• locuslab / robust_overfitting
  ☆157Updated 4 years ago
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆150Updated 4 years ago
• zjfheart / Friendly-Adversarial-Training
  Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)
  ☆125Updated last year
• imrahulr / adversarial_robustness_pytorch
  Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…
  ☆97Updated 3 years ago
• locuslab / fast_adversarial
  [ICLR 2020] A repository for extremely fast adversarial training using FGSM
  ☆444Updated 10 months ago
• mahyarnajibi / FreeAdversarialTraining
  PyTorch Implementation of Adversarial Training for Free!
  ☆247Updated 3 years ago
• ylsung / pytorch-adversarial-training
  PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.
  ☆251Updated 4 years ago
• csdongxian / AWP
  Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"
  ☆181Updated 4 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 4 years ago
• yaodongyu / TRADES
  TRADES (TRadeoff-inspired Adversarial DEfense via Surrogate-loss minimization)
  ☆542Updated 2 years ago
• VITA-Group / Adversarial-Contrastive-Learning
  [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang
  ☆114Updated 3 years ago
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆142Updated 5 years ago
• wanglouis49 / pytorch-adversarial_box
  PyTorch library for adversarial attack and training
  ☆145Updated 6 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• P2333 / Max-Mahalanobis-Training
  Max Mahalanobis Training (ICML 2018 + ICLR 2020)
  ☆90Updated 4 years ago
• tingxueronghua / pytorch-classification-advprop
  ☆108Updated 3 years ago
• P2333 / Papers-of-Robust-ML
  Related papers for robust machine learning
  ☆566Updated 2 years ago
• P2333 / SCORE
  A Self-Consistent Robust Error (ICML 2022)
  ☆68Updated last year
• uclaml / RayS
  RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
  ☆56Updated 4 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆73Updated last year
• Harry24k / PGD-pytorch
  A pytorch implementation of "Towards Deep Learning Models Resistant to Adversarial Attacks"
  ☆155Updated 5 years ago
• CUAI / Intermediate-Level-Attack
  [ICCV 2019] Enhancing Adversarial Example Transferability with an Intermediate Level Attack (https://arxiv.org/abs/1907.10823)
  ☆78Updated 5 years ago
• RulinShao / on-the-adversarial-robustness-of-visual-transformer
  Code for the paper "On the Adversarial Robustness of Visual Transformers"
  ☆58Updated 3 years ago
• tao-bai / attack-and-defense-methods
  A curated list of papers on adversarial machine learning (adversarial examples and defense methods).
  ☆210Updated 3 years ago
• ermongroup / ODS
  Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"
  ☆53Updated 4 years ago
• dongyp13 / Translation-Invariant-Attacks
  The translation-invariant adversarial attack method to improve the transferability of adversarial examples.
  ☆141Updated last year
• cg563 / simple-blackbox-attack
  Code for ICML 2019 paper "Simple Black-box Adversarial Attacks"
  ☆198Updated 2 years ago
• csdongxian / skip-connections-matter
  Codes for ICLR 2020 paper "Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets"
  ☆70Updated 4 years ago
• cihangxie / DI-2-FGSM
  Improving Transferability of Adversarial Examples with Input Diversity
  ☆164Updated 6 years ago
• MadryLab / cifar10_challenge
  A challenge to explore adversarial robustness of neural networks on CIFAR10.
  ☆498Updated 3 years ago