Alternatives and similar repositories for InNOutRobustness:

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

• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 2 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 4 years ago
• JHL-HUST / RLFAT
  ☆13Updated 4 years ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆55Updated 3 years ago
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 2 years ago
• dedeswim / vits-robustness-torch
  Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]
  ☆53Updated 2 years ago
• fra31 / robust-finetuning
  Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"
  ☆18Updated 2 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• ShawnXYang / AT_HE
  ☆35Updated 4 years ago
• goldblum / AdversariallyRobustDistillation
  Pytorch implementation of Adversarially Robust Distillation (ARD)
  ☆59Updated 5 years ago
• DequanWang / dent
  Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
  ☆38Updated 3 years ago
• MadryLab / blackbox-bandits
  Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"
  ☆63Updated 5 years ago
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 3 years ago
• BorealisAI / mma_training
  Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
  ☆34Updated 4 years ago
• imrahulr / hat
  Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off
  ☆29Updated 2 years ago
• 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
• watml / fast-wasserstein-adversarial
  Implementation of Wasserstein adversarial attacks.
  ☆23Updated 4 years 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
• pdejorge / N-FGSM
  Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)
  ☆25Updated 2 years ago
• Harry24k / adversarial-defenses-pytorch
  PyTorch implementations of Adversarial defenses and utils.
  ☆34Updated last year
• cihangxie / SmoothAdversarialTraining
  Smooth Adversarial Training
  ☆67Updated 4 years ago
• val-iisc / GAMA-GAT
  Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020
  ☆26Updated 4 years ago
• pralab / ImageNet-Patch
  ☆39Updated last year
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 4 years ago
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆26Updated 7 months ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• P2333 / Rectified-Rejection
  Coupling rejection strategy against adversarial attacks (CVPR 2022)
  ☆28Updated 3 years ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 3 years ago
• HanshuYAN / CIFS
  CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
  ☆20Updated 3 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆36Updated 2 months ago