Alternatives and similar repositories for Bayesian-Adversarial-Learning

Users that are interested in Bayesian-Adversarial-Learning are comparing it to the libraries listed below

• hmdolatabadi / AdvFlow
  [NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".
  ☆49Updated 2 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
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 7 years ago
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆44Updated 5 years ago
• YyzHarry / ME-Net
  [ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
  ☆54Updated 3 months ago
• rubinxin / BayesOpt_Attack
  Targeted black-box adversarial attack using Bayesian Optimization
  ☆38Updated 5 years ago
• VITA-Group / Once-for-All-Adversarial-Training
  [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…
  ☆44Updated 4 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆28Updated 4 years ago
• s-huu / TurningWeaknessIntoStrength
  Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength
  ☆38Updated 5 years ago
• locuslab / projected_sinkhorn
  ☆88Updated last year
• ZiangYan / subspace-attack.pytorch
  Implementation of our NeurIPS 2019 paper: Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
  ☆10Updated 6 years ago
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 4 years ago
• xuanqing94 / BayesianDefense
  Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
  ☆61Updated 6 years ago
• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆66Updated 6 years ago
• ShawnXYang / AT_HE
  ☆35Updated 5 years ago
• MadryLab / robust_representations
  Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"
  ☆164Updated 5 years ago
• columbia / Metric_Learning_Adversarial_Robustness
  Code for NeurIPS 2019 Paper
  ☆48Updated 5 years ago
• YunseokJANG / l2l-da
  Repository for our ICCV 2019 paper: Adversarial Defense via Learning to Generate Diverse Attacks
  ☆22Updated 4 years ago
• ZhaoyangLyu / POPQORN
  An Algorithm to Quantify Robustness of Recurrent Neural Networks
  ☆49Updated 5 years ago
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆141Updated 5 years ago
• P2333 / Rectified-Rejection
  Coupling rejection strategy against adversarial attacks (CVPR 2022)
  ☆29Updated 3 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 5 years ago
• Bai-Li / STN-Code
  Code for Stability Training with Noise (STN)
  ☆22Updated 5 years ago
• kkelchte / task_free_continual_learning
  This repository demonstrates the application of our proposed task-free continual learning method on a synthetic experiment.
  ☆13Updated 6 years ago
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 3 years ago
• P2333 / Reverse-Cross-Entropy
  Reverse Cross Entropy for Adversarial Detection (NeurIPS 2018)
  ☆47Updated 4 years ago
• joeybose / Adversarial-Example-Games
  Code for Adversarial Example Games NeurIPS 2020 Paper
  ☆27Updated last year
• dtak / adversarial-robustness-public
  Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing the…
  ☆55Updated 3 years ago
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆25Updated last year