Alternatives and similar repositories for Bayesian-Adversarial-Learning

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

• neale / HyperGAN
  Generative Model for Neural Networks
  ☆24Updated 4 years ago
• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆66Updated 5 years ago
• MadryLab / spatial-pytorch
  Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).
  ☆26Updated 5 years ago
• YunseokJANG / l2l-da
  Repository for our ICCV 2019 paper: Adversarial Defense via Learning to Generate Diverse Attacks
  ☆22Updated 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
• s-huu / TurningWeaknessIntoStrength
  Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength
  ☆38Updated 5 years ago
• rubinxin / BayesOpt_Attack
  Targeted black-box adversarial attack using Bayesian Optimization
  ☆37Updated 4 years ago
• xu-ji / ARM
  Automatic Recall Machines: Internal Replay, Continual Learning and the Brain
  ☆11Updated 4 years ago
• YyzHarry / ME-Net
  [ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
  ☆54Updated last week
• ytsmiling / lmt
  Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
  ☆34Updated 6 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• hmdolatabadi / AdvFlow
  [NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".
  ☆47Updated last year
• ZiangYan / subspace-attack.pytorch
  Implementation of our NeurIPS 2019 paper: Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
  ☆10Updated 5 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• P2333 / Reverse-Cross-Entropy
  Reverse Cross Entropy for Adversarial Detection (NeurIPS 2018)
  ☆45Updated 4 years ago
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 4 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• nexuslrf / knowledge_consistency
  Codes for our ICLR2020 paper: Knowledge Consistency between Neural Networks and Beyond
  ☆16Updated 5 years ago
• locuslab / projected_sinkhorn
  ☆87Updated 10 months ago
• RuntianZ / macer
  MACER: MAximizing CErtified Radius (ICLR 2020)
  ☆30Updated 5 years ago
• uds-lsv / evaluating-logit-pairing-methods
  Logit Pairing Methods Can Fool Gradient-Based Attacks [NeurIPS 2018 Workshop on Security in Machine Learning]
  ☆19Updated 6 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 3 years ago
• chingyaoc / fair-mixup
  ICLR 2021, Fair Mixup: Fairness via Interpolation
  ☆56Updated 3 years ago
• jhjacobsen / fully-invertible-revnet
  ☆31Updated 4 years ago
• locuslab / robust_union
  [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.
  ☆26Updated 10 months ago
• kkelchte / task_free_continual_learning
  This repository demonstrates the application of our proposed task-free continual learning method on a synthetic experiment.
  ☆13Updated 5 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆73Updated last year
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆45Updated 5 years ago
• jh-jeong / smoothing-consistency
  Code for the paper "Consistency Regularization for Certified Robustness of Smoothed Classifiers" (NeurIPS 2020)
  ☆34Updated 4 years ago