Alternatives and similar repositories for Cost-Sensitive-Robustness

Users that are interested in Cost-Sensitive-Robustness are comparing it to the libraries listed below

• alvinchangw / IGAM_CVPR2020
  Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)
  ☆16Updated 2 years ago
• hendrycks / fooling
  Code for the Adversarial Image Detectors and a Saliency Map
  ☆12Updated 8 years ago
• cetmann / robustness-interpretability
  Code for the Paper 'On the Connection Between Adversarial Robustness and Saliency Map Interpretability' by C. Etmann, S. Lunz, P. Maass, …
  ☆16Updated 6 years ago
• yk / icml19_public
  ☆22Updated 4 years ago
• xuanqing94 / BayesianDefense
  Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
  ☆62Updated 5 years ago
• enyac-group / Renofeation
  ☆19Updated 3 years ago
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆45Updated 5 years ago
• deepgenerativeclassifier / DeepBayes
  Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"
  ☆23Updated 6 years ago
• mndu / guided-feature-inversion
  PyTorch code for KDD 18 paper: Towards Explanation of DNN-based Prediction with Guided Feature Inversion
  ☆21Updated 6 years ago
• dtak / adversarial-robustness-public
  Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing the…
  ☆55Updated 2 years ago
• bhanML / SIGUA
  ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
  ☆15Updated 4 years ago
• schzhu / learning-adversarially-robust-representations
  Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2…
  ☆23Updated 4 years ago
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 2 years ago
• tcwangshiqi-columbia / Interval-Attack
  Interval attacks (adversarial ML)
  ☆21Updated 5 years ago
• Ivan1248 / Parseval-networks
  An (imperfect) implementation of wide resnets and Parseval regularization
  ☆9Updated 5 years ago
• LTS4 / hold-me-tight
  Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"
  ☆22Updated 3 years ago
• houshd / TS_Adv
  Codebase for the paper "Adversarial Attacks on Time Series"
  ☆19Updated 6 years ago
• AlanChou / Adversarial-Training-for-Free
  Unofficial implementation of the paper 'Adversarial Training for Free'
  ☆22Updated 6 years ago
• locuslab / perturbation_learning
  Learning perturbation sets for robust machine learning
  ☆65Updated 3 years ago
• MadryLab / robustness_lib
  ☆11Updated 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
• StephanZheng / neural-fingerprinting
  ☆29Updated 6 years ago
• MadryLab / adversarial_spatial
  Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.
  ☆49Updated 5 years ago
• ZhaoyangLyu / POPQORN
  An Algorithm to Quantify Robustness of Recurrent Neural Networks
  ☆48Updated 5 years ago
• max-andr / cross-lipschitz
  Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]
  ☆18Updated 7 years ago
• BorealisAI / mma_training
  Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
  ☆34Updated 5 years ago
• max-andr / provably-robust-boosting
  Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]
  ☆50Updated 5 years ago
• jhayes14 / black-box-attacks
  Comparison of gradient estimation techniques for black-box adversarial examples
  ☆11Updated 6 years ago
• max-andr / provable-robustness-max-linear-regions
  Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]
  ☆32Updated 4 years ago
• Bai-Li / STN-Code
  Code for Stability Training with Noise (STN)
  ☆22Updated 4 years ago