Alternatives and similar repositories for IAD

Users that are interested in IAD are comparing it to the libraries listed below

• val-iisc / NuAT
  Towards Efficient and Effective Adversarial Training, NeurIPS 2021
  ☆17Updated 3 years ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 4 years ago
• lhfowl / adversarial_poisons
  ☆54Updated 4 years ago
• PKU-ML / CFA
  ☆20Updated 9 months ago
• imrahulr / adversarial_robustness_pytorch
  Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…
  ☆98Updated 3 years ago
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆152Updated 5 years ago
• jiaxiaojunQAQ / FGSM-PGI
  Code for Prior-Guided Adversarial Initialization for Fast Adversarial Training (ECCV2022)
  ☆28Updated 3 years ago
• ZhengyuZhao / Targeted-Transfer
  Simple yet effective targeted transferable attack (NeurIPS 2021)
  ☆51Updated 3 years ago
• nmndeep / revisiting-at
  [NeurIPS 2023] Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threa…
  ☆39Updated last year
• Alexkael / Randomized-Adversarial-Training
  ☆31Updated last year
• ChaojianYu / Robust-Weight-Perturbation
  Implementation for <Robust Weight Perturbation for Adversarial Training> in IJCAI'22.
  ☆16Updated 3 years ago
• wzekai99 / DM-Improves-AT
  Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)
  ☆146Updated 2 years ago
• zibojia / RSLAD
  This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"
  ☆46Updated 4 years ago
• SCLBD / Transfer_attack_RAP
  ☆35Updated 3 years ago
• kaiwenzha / contrastive-poisoning
  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
  ☆33Updated 2 years ago
• renjie3 / TUE
  Code for Transferable Unlearnable Examples
  ☆23Updated 2 years ago
• Saehyung-Lee / cifar10_challenge
  Code for the CVPR 2020 article "Adversarial Vertex mixup: Toward Better Adversarially Robust Generalization"
  ☆13Updated 5 years ago
• bymavis / CAS_ICLR2021
  ☆58Updated 3 years ago
• xherdan76 / A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
  A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)
  ☆31Updated 3 years ago
• rkteddy / channel-Lipschitzness-based-pruning
  Source code for ECCV 2022 Poster: Data-free Backdoor Removal based on Channel Lipschitzness
  ☆34Updated 3 years ago
• kai-wen-yang / CD-VAE
  [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
  ☆46Updated 3 years ago
• ZhengyuZhao / TransferAttackEval
  Revisiting Transferable Adversarial Images (TPAMI 2025)
  ☆139Updated 3 months ago
• TLMichael / Delusive-Adversary
  [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
  ☆32Updated 4 years ago
• lafeat / apbench
  APBench: A Unified Availability Poisoning Attack and Defenses Benchmark (TMLR 08/2024)
  ☆46Updated 8 months ago
• Alan-Qin / Transfer_attack_RAP
  Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation (NeurIPS 2022)
  ☆33Updated 3 years ago
• ChaojianYu / Understanding-Robust-Overfitting
  Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.
  ☆12Updated 3 years ago
• JindongGu / Awesome_Adversarial_Transferability
  A curated list of papers for the transferability of adversarial examples
  ☆75Updated last year
• HanxunH / CognitiveDistillation
  [ICLR2023] Distilling Cognitive Backdoor Patterns within an Image
  ☆36Updated 2 months ago
• liuye6666 / adaptive_auto_attack
  Adversarial Robustness, White-box, Adversarial Attack
  ☆52Updated 3 years ago
• YiZeng623 / frequency-backdoor
  ICCV 2021, We find most existing triggers of backdoor attacks in deep learning contain severe artifacts in the frequency domain. This Rep…
  ☆46Updated 3 years ago