Alternatives and similar repositories for CURE_robustness:

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

• imrahulr / adversarial_robustness_pytorch
  Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…
  ☆95Updated 2 years ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 3 years ago
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆144Updated 4 years ago
• watml / fast-wasserstein-adversarial
  Implementation of Wasserstein adversarial attacks.
  ☆23Updated 4 years ago
• RulinShao / on-the-adversarial-robustness-of-visual-transformer
  Code for the paper "On the Adversarial Robustness of Visual Transformers"
  ☆55Updated 3 years ago
• haizhongzheng / ATTA
  ATTA (Efficient Adversarial Training with Transferable Adversarial Examples)
  ☆35Updated 4 years ago
• Jack-lx-jiang / MD_attacks
  Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness. (MD attacks)
  ☆11Updated 4 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆36Updated 2 months ago
• VITA-Group / Alleviate-Robust-Overfitting
  [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…
  ☆46Updated 3 years ago
• uclaml / RayS
  RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
  ☆56Updated 4 years ago
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆140Updated 4 years ago
• lhfowl / adversarial_poisons
  ☆48Updated 3 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• goldblum / AdversariallyRobustDistillation
  Pytorch implementation of Adversarially Robust Distillation (ARD)
  ☆59Updated 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
• nmndeep / revisiting-at
  [NeurIPS 2023] Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threa…
  ☆38Updated 2 months ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆55Updated 3 years ago
• wielandbrendel / adaptive_attacks_paper
  Code for "On Adaptive Attacks to Adversarial Example Defenses"
  ☆86Updated 4 years ago
• qizhangli / linbp-attack
  Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.
  ☆42Updated 2 years ago
• hirokiadachi / Adversarial-vertex-mixup-pytorch
  ☆10Updated 3 years ago
• wjyouch / bilateral-adversarial-training
  ☆16Updated 5 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆72Updated 8 months ago
• vtddggg / CAA
  The implementation of our paper: Composite Adversarial Attacks (AAAI2021)
  ☆30Updated 3 years ago
• aamir-mustafa / pcl-adversarial-defense
  Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019
  ☆59Updated 5 years ago
• karandwivedi42 / adversarial
  Pytorch - Adversarial Training
  ☆26Updated 6 years ago
• Annonymous-repos / attacks-in-pytorch
  Reproduces BPDA attack in pytorch
  ☆13Updated 5 years ago
• bymavis / CAS_ICLR2021
  ☆57Updated 2 years ago
• yigitcankaya / augmentation_mia
  The source code for ICML2021 paper When Does Data Augmentation Help With Membership Inference Attacks?
  ☆8Updated 3 years ago
• fra31 / fab-attack
  Code for FAB-attack
  ☆32Updated 4 years ago
• HanxunH / RobustWRN
  [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
  ☆34Updated 7 months ago