robust-ml / robustmlLinks
Interfaces for defining Robust ML models and precisely specifying the threat models under which they claim to be secure.
☆62Updated 6 years ago
Alternatives and similar repositories for robustml
Users that are interested in robustml are comparing it to the libraries listed below
Sorting:
- LaTeX source for the paper "On Evaluating Adversarial Robustness"☆255Updated 4 years ago
- A community-run reference for state-of-the-art adversarial example defenses.☆50Updated 11 months ago
- Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"☆227Updated 5 years ago
- Code for "Robustness May Be at Odds with Accuracy"☆91Updated 2 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆31Updated 5 years ago
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 6 years ago
- Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"☆186Updated 5 years ago
- A method for training neural networks that are provably robust to adversarial attacks.☆390Updated 3 years ago
- Benchmark for LP-relaxed robustness verification of ReLU-networks☆42Updated 6 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆80Updated last year
- ☆26Updated 2 years ago
- Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]☆50Updated 5 years ago
- Adversarially Robust Neural Network on MNIST.☆63Updated 3 years ago
- ☆88Updated last year
- Robust Vision Benchmark☆23Updated 7 years ago
- NIPS Adversarial Vision Challenge☆41Updated 7 years ago
- Analysis of Adversarial Logit Pairing☆60Updated 7 years ago
- Code for "Detecting Adversarial Samples from Artifacts" (Feinman et al., 2017)☆111Updated 7 years ago
- A certifiable defense against adversarial examples by training neural networks to be provably robust☆221Updated last year
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆38Updated 5 years ago
- A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturb…☆12Updated 5 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆51Updated 5 years ago
- This repository contains a simple implementation of Interval Bound Propagation (IBP) using TensorFlow: https://arxiv.org/abs/1810.12715☆162Updated 5 years ago
- Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs☆97Updated 4 years ago
- Towards Reverse-Engineering Black-Box Neural Networks, ICLR'18☆55Updated 6 years ago
- Code for "Black-box Adversarial Attacks with Limited Queries and Information" (http://arxiv.org/abs/1804.08598)☆180Updated 4 years ago
- Interval attacks (adversarial ML)☆21Updated 6 years ago
- Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTor…☆98Updated 4 years ago
- Ensemble Adversarial Training on MNIST☆121Updated 8 years ago
- CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is a robustness metric for deep neural networks☆63Updated 4 years ago