Alternatives and similar repositories for AdversarialAndDimensionality

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

• microsoft / denoised-smoothing
  Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
  ☆102Updated 4 years ago
• ddkang / advex-uar
  Code for "Testing Robustness Against Unforeseen Adversaries"
  ☆80Updated last year
• ftramer / Excessive-Invariance
  Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"
  ☆25Updated 5 years ago
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆25Updated last year
• locuslab / projected_sinkhorn
  ☆88Updated last year
• Hadisalman / smoothing-adversarial
  Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"
  ☆228Updated 6 years ago
• MadryLab / robust-features-code
  Code for "Robustness May Be at Odds with Accuracy"
  ☆91Updated 2 years ago
• MadryLab / BREEDS-Benchmarks
  ☆56Updated 5 years ago
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆141Updated 5 years ago
• wronnyhuang / gen-viz
  Code for the paper "Understanding Generalization through Visualizations"
  ☆65Updated 5 years ago
• P2333 / Max-Mahalanobis-Training
  Max Mahalanobis Training (ICML 2018 + ICLR 2020)
  ☆90Updated 5 years ago
• max-andr / provable-robustness-max-linear-regions
  Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]
  ☆31Updated 5 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• MadryLab / constructed-datasets
  Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"
  ☆187Updated 5 years ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆56Updated 4 years ago
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 3 years ago
• MadryLab / spatial-pytorch
  Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).
  ☆26Updated 6 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆74Updated last year
• ashafahi / free_adv_train
  Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural trai…
  ☆177Updated last year
• P2333 / Adaptive-Diversity-Promoting
  Adversarial Defense for Ensemble Models (ICML 2019)
  ☆61Updated 5 years ago
• locuslab / robust_overfitting
  ☆162Updated 4 years ago
• MadryLab / adversarial_spatial
  Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.
  ☆49Updated 6 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆96Updated 4 years ago
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆42Updated 2 years ago
• uclaml / RayS
  RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
  ☆56Updated 5 years ago
• bethgelab / AnalysisBySynthesis
  Adversarially Robust Neural Network on MNIST.
  ☆63Updated 4 years ago
• evaluating-adversarial-robustness / adv-eval-paper
  LaTeX source for the paper "On Evaluating Adversarial Robustness"
  ☆259Updated 4 years ago
• fra31 / fab-attack
  Code for FAB-attack
  ☆34Updated 5 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 5 years ago
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 4 years ago