Hadisalman / smoothing-adversarial
Code for our NeurIPS 2019 *spotlight* "Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers"
☆225Updated 5 years ago
Alternatives and similar repositories for smoothing-adversarial
Users that are interested in smoothing-adversarial are comparing it to the libraries listed below
Sorting:
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆52Updated 4 years ago
- Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs☆97Updated 4 years ago
- Provable adversarial robustness at ImageNet scale☆388Updated 5 years ago
- ☆87Updated 9 months ago
- Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"☆187Updated 4 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆141Updated 5 years ago
- Code for "Robustness May Be at Odds with Accuracy"☆91Updated 2 years ago
- LaTeX source for the paper "On Evaluating Adversarial Robustness"☆255Updated 4 years ago
- ☆157Updated 4 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆81Updated 9 months ago
- Pytorch Adversarial Attack Framework☆78Updated 6 years ago
- Adversarially Robust Neural Network on MNIST.☆64Updated 3 years ago
- [ICLR 2020] A repository for extremely fast adversarial training using FGSM☆443Updated 9 months ago
- Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"☆128Updated 5 years ago
- Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"☆159Updated 5 years ago
- Code for the paper "Understanding Generalization through Visualizations"☆60Updated 4 years ago
- A method for training neural networks that are provably robust to adversarial attacks.☆387Updated 3 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆38Updated 5 years ago
- RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)☆56Updated 4 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆73Updated 11 months ago
- Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"☆134Updated 4 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 3 years ago
- Code for the unrestricted adversarial examples paper (NeurIPS 2018)☆64Updated 5 years ago
- Blackbox attacks for deep neural network models☆70Updated 6 years ago
- Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural trai…☆174Updated last year
- Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"☆147Updated 4 years ago
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 5 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆58Updated 5 years ago
- ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks☆169Updated 3 years ago
- Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle☆175Updated 9 months ago