Alternatives and similar repositories for Adversarial-Example-Games:

Users that are interested in Adversarial-Example-Games 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
• 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
• watml / fast-wasserstein-adversarial
  Implementation of Wasserstein adversarial attacks.
  ☆23Updated 4 years ago
• sunblaze-ucb / curriculum-adversarial-training-CAT
  ☆14Updated 5 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
• goldblum / AdversariallyRobustDistillation
  Pytorch implementation of Adversarially Robust Distillation (ARD)
  ☆59Updated 5 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 4 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆36Updated 2 months ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 3 years ago
• JHL-HUST / RLFAT
  ☆13Updated 4 years ago
• RuntianZ / macer
  MACER: MAximizing CErtified Radius (ICLR 2020)
  ☆28Updated 5 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
• ShawnXYang / AT_HE
  ☆35Updated 4 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
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆26Updated 6 months ago
• val-iisc / GAMA-GAT
  Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020
  ☆26Updated 4 years ago
• fra31 / sparse-rs
  Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
  ☆45Updated 2 years ago
• DequanWang / dent
  Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
  ☆38Updated 3 years ago
• rubinxin / BayesOpt_Attack
  Targeted black-box adversarial attack using Bayesian Optimization
  ☆37Updated 4 years ago
• fra31 / evaluating-adaptive-test-time-defenses
  ☆22Updated last year
• nsfzyzz / boundary_thickness
  [NeurIPS 2020] code for "Boundary thickness and robustness in learning models"
  ☆19Updated 4 years ago
• HanshuYAN / CIFS
  CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
  ☆20Updated 3 years ago
• val-iisc / DAJAT
  Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)
  ☆16Updated last year
• cassidylaidlaw / ReColorAdv
  ReColorAdv and other attacks from the NeurIPS 2019 paper "Functional Adversarial Attacks"
  ☆37Updated 2 years ago
• YisenWang / dynamic_adv_training
  Code for ICML2019 Paper "On the Convergence and Robustness of Adversarial Training"
  ☆34Updated 4 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆72Updated 8 months ago
• MadryLab / spatial-pytorch
  Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).
  ☆26Updated 5 years ago
• uclaml / RayS
  RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
  ☆56Updated 4 years ago
• yjhuangcd / local-lipschitz
  Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).
  ☆23Updated 2 years ago