Alternatives and similar repositories for meta-adversarial-training

Users that are interested in meta-adversarial-training are comparing it to the libraries listed below

• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆56Updated 3 years ago
• alevine0 / patchSmoothing
  Code for the paper "(De)Randomized Smoothing for Certifiable Defense against Patch Attacks" by Alexander Levine and Soheil Feizi.
  ☆17Updated 3 years ago
• Bai-Li / STN-Code
  Code for Stability Training with Noise (STN)
  ☆22Updated 4 years ago
• DequanWang / dent
  Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
  ☆39Updated 4 years ago
• pralab / ImageNet-Patch
  ☆41Updated last year
• MadryLab / blackbox-bandits
  Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"
  ☆64Updated 5 years ago
• wielandbrendel / adaptive_attacks_paper
  Code for "On Adaptive Attacks to Adversarial Example Defenses"
  ☆87Updated 4 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆74Updated last year
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆96Updated 4 years ago
• microsoft / denoised-smoothing
  Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
  ☆97Updated 4 years ago
• Ping-C / certifiedpatchdefense
  Repository for Certified Defenses for Adversarial Patch ICLR-2020
  ☆34Updated 5 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 5 years ago
• joeybose / Adversarial-Example-Games
  Code for Adversarial Example Games NeurIPS 2020 Paper
  ☆27Updated 10 months ago
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆142Updated 5 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 3 years ago
• hmdolatabadi / AdvFlow
  [NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".
  ☆48Updated 2 years ago
• goldblum / AdversariallyRobustDistillation
  Pytorch implementation of Adversarially Robust Distillation (ARD)
  ☆59Updated 6 years ago
• val-iisc / OAAT
  Official Code for Scaling Adversarial Training to Large Perturbation Bounds (ECCV-2022)
  ☆11Updated 2 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆24Updated 3 years ago
• nvedant07 / Fairness-Through-Robustness
  Official code for FAccT'21 paper "Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning" https://arxiv.org/abs…
  ☆13Updated 4 years ago
• Harry24k / adversarial-defenses-pytorch
  PyTorch implementations of Adversarial defenses and utils.
  ☆34Updated last year
• dongyp13 / Adversarial-Distributional-Training
  Adversarial Distributional Training (NeurIPS 2020)
  ☆63Updated 4 years ago
• hsouri / Sleeper-Agent
  ☆67Updated last year
• 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 3 years ago
• locuslab / robust_overfitting
  ☆158Updated 4 years ago
• nesl / adversarial_genattack
  ☆56Updated 2 years ago
• uclaml / RayS
  RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
  ☆56Updated 4 years ago
• imrahulr / hat
  Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off
  ☆33Updated 3 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…
  ☆47Updated 3 years ago
• ermongroup / ODS
  Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"
  ☆53Updated 4 years ago