MadryLab / robust-features-code
Code for "Robustness May Be at Odds with Accuracy"
☆91Updated 2 years ago
Alternatives and similar repositories for robust-features-code:
Users that are interested in robust-features-code are comparing it to the libraries listed below
- Investigating the robustness of state-of-the-art CNN architectures to simple spatial transformations.☆49Updated 5 years ago
- Provable Robustness of ReLU networks via Maximization of Linear Regions [AISTATS 2019]☆32Updated 4 years ago
- Datasets for the paper "Adversarial Examples are not Bugs, They Are Features"☆187Updated 4 years ago
- ☆87Updated 9 months ago
- A PyTorch baseline attack example for the NIPS 2017 adversarial competition☆85Updated 7 years ago
- Analysis of Adversarial Logit Pairing☆60Updated 6 years ago
- Notebooks for reproducing the paper "Computer Vision with a Single (Robust) Classifier"☆128Updated 5 years ago
- NIPS Adversarial Vision Challenge☆41Updated 6 years ago
- Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."☆34Updated 6 years ago
- Code for FAB-attack☆32Updated 4 years ago
- Ensemble Adversarial Training on MNIST☆121Updated 7 years ago
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆141Updated 5 years ago
- Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"☆159Updated 5 years ago
- Spatially Transformed Adversarial Examples with TensorFlow☆74Updated 6 years ago
- Pytorch Adversarial Attack Framework☆78Updated 6 years ago
- Adversarially Robust Neural Network on MNIST.☆64Updated 3 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆59Updated 5 years ago
- Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"☆134Updated 4 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆81Updated 9 months ago
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆26Updated 9 months ago
- Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).☆26Updated 5 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- LaTeX source for the paper "On Evaluating Adversarial Robustness"☆255Updated 4 years ago
- Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation [NeurIPS 2017]☆18Updated 7 years ago
- Randomized Smoothing of All Shapes and Sizes (ICML 2020).☆52Updated 4 years ago
- Official implementation for paper: A New Defense Against Adversarial Images: Turning a Weakness into a Strength☆38Updated 5 years ago
- Benchmark for LP-relaxed robustness verification of ReLU-networks☆41Updated 6 years ago
- Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs☆97Updated 4 years ago
- ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks☆169Updated 3 years ago
- AAAI 2019 oral presentation☆50Updated 2 weeks ago