Alternatives and similar repositories for sauron

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

• max-andr / provable-robustness-max-linear-regions
  Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]
  ☆32Updated 5 years ago
• max-andr / cross-lipschitz
  Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]
  ☆18Updated 7 years ago
• deepgenerativeclassifier / DeepBayes
  Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"
  ☆23Updated 6 years ago
• MadryLab / robustness_lib
  ☆11Updated 5 years ago
• MadryLab / adversarial_spatial
  Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.
  ☆49Updated 5 years ago
• microsoft / denoised-smoothing
  Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
  ☆97Updated 4 years ago
• ddkang / advex-uar
  Code for "Testing Robustness Against Unforeseen Adversaries"
  ☆81Updated last year
• ftramer / Excessive-Invariance
  Source code for the paper "Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness"
  ☆25Updated 5 years ago
• adversarial-robustness-benchmark / adversarial-robustness-benchmark
  ☆18Updated 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
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 2 years ago
• locuslab / projected_sinkhorn
  ☆88Updated last year
• MadryLab / robust-features-code
  Code for "Robustness May Be at Odds with Accuracy"
  ☆91Updated 2 years ago
• facebookresearch / fisher_information_loss
  This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"
  ☆50Updated 3 years ago
• tonyduan / rs4a
  Randomized Smoothing of All Shapes and Sizes (ICML 2020).
  ☆52Updated 5 years ago
• Hadisalman / robust-verify-benchmark
  Benchmark for LP-relaxed robustness verification of ReLU-networks
  ☆41Updated 6 years ago
• labsix / adversarial-logit-pairing-analysis
  Analysis of Adversarial Logit Pairing
  ☆60Updated 6 years ago
• jonasrauber / linear-region-attack
  A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…
  ☆12Updated 5 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆42Updated 2 years ago
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆45Updated 5 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
• jhayes14 / black-box-attacks
  Comparison of gradient estimation techniques for black-box adversarial examples
  ☆11Updated 6 years ago
• MadryLab / robustness_applications
  Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"
  ☆128Updated 5 years ago
• 1202kbs / Robustness-and-Interpretability
  Official repository for "Bridging Adversarial Robustness and Gradient Interpretability".
  ☆30Updated 6 years ago
• tginart / deletion-efficient-kmeans
  Research prototype of deletion efficient k-means algorithms
  ☆24Updated 5 years ago
• ajiljalal / manifold-defense
  ☆21Updated last year
• ytsmiling / lmt
  Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
  ☆34Updated 6 years ago
• robust-ml / robust-ml.github.io
  A community-run reference for state-of-the-art adversarial example defenses.
  ☆50Updated 9 months ago
• StephanZheng / neural-fingerprinting
  ☆29Updated 6 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