Alternatives and similar repositories for Robustness-and-Interpretability

Users that are interested in Robustness-and-Interpretability are comparing it to the libraries listed below

• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• MadryLab / dataset-replication-analysis
  ☆25Updated 5 years ago
• StephanZheng / neural-fingerprinting
  ☆29Updated 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
• 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
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 5 years ago
• ruthcfong / perturb_explanations
  Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"
  ☆31Updated 5 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 7 years ago
• ddkang / advex-uar
  Code for "Testing Robustness Against Unforeseen Adversaries"
  ☆81Updated 11 months ago
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆45Updated 5 years ago
• MadryLab / robustness_lib
  ☆11Updated 5 years ago
• ruthcfong / net2vec
  Code for Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks
  ☆30Updated 7 years ago
• YunseokJANG / l2l-da
  Repository for our ICCV 2019 paper: Adversarial Defense via Learning to Generate Diverse Attacks
  ☆22Updated 3 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• MadryLab / robustness_applications
  Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"
  ☆128Updated 5 years ago
• MadryLab / ImageNetMultiLabel
  Fine-grained ImageNet annotations
  ☆29Updated 5 years ago
• hongyanz / TRADES-smoothing
  [JMLR] TRADES + random smoothing for certifiable robustness
  ☆14Updated 4 years ago
• ajiljalal / manifold-defense
  ☆21Updated 11 months ago
• MadryLab / adversarial_spatial
  Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.
  ☆49Updated 5 years ago
• 962086838 / code-for-Asymmetric-Valley
  This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".
  ☆14Updated 5 years ago
• HaohanWang / PAR_experiments
  Learning Robust Global Representations by Penalizing Local Predictive Power (NeurIPS 2019))
  ☆18Updated 2 years ago
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆35Updated 4 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
• MSusik / Inhibited-softmax
  Repository with code for paper "Inhibited Softmax for Uncertainty Estimation in Neural Networks"
  ☆25Updated 6 years ago
• max-andr / cross-lipschitz
  Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]
  ☆18Updated 7 years ago
• chingyaoc / estimating-generalization
  ICML 2020, Estimating Generalization under Distribution Shifts via Domain-Invariant Representations
  ☆23Updated 4 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆42Updated 2 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• BorealisAI / bre-gan
  Code for ICLR2018 paper: Improving GAN Training via Binarized Representation Entropy (BRE) Regularization - Y. Cao · W Ding · Y.C. Lui · …
  ☆20Updated 7 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