anonymous-sushi-armadillo / fast_is_better_than_free_CIFAR10
☆12Updated 9 months ago
Alternatives and similar repositories for fast_is_better_than_free_CIFAR10:
Users that are interested in fast_is_better_than_free_CIFAR10 are comparing it to the libraries listed below
- Strongest attack against Feature Scatter and Adversarial Interpolation☆25Updated 5 years ago
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆27Updated 4 years ago
- Feature Scattering Adversarial Training (NeurIPS19)☆73Updated 10 months ago
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆96Updated 3 years ago
- Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"☆53Updated 4 years ago
- Implementation of Wasserstein adversarial attacks.☆23Updated 4 years ago
- MACER: MAximizing CErtified Radius (ICLR 2020)☆29Updated 5 years ago
- Pytorch - Adversarial Training☆26Updated 6 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 5 years ago
- Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…☆96Updated 3 years ago
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Updated 3 years ago
- Adversarial Distributional Training (NeurIPS 2020)☆63Updated 4 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆46Updated 3 years ago
- the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral☆59Updated 4 years ago
- ☆48Updated 4 years ago
- ☆58Updated 2 years ago
- ☆16Updated 5 years ago
- Code for FAB-attack☆32Updated 4 years ago
- Code for the paper "On the Adversarial Robustness of Visual Transformers"☆56Updated 3 years ago
- Code for Black-Box Adversarial Attack with Transferable Model-based Embedding☆57Updated 4 years ago
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆38Updated 3 years ago
- ☆35Updated 4 years ago
- [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks☆34Updated 9 months ago
- Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…☆92Updated 2 years ago
- Codes for reproducing query-efficient black-box attacks in “AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking B…☆57Updated 5 years ago
- Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".☆55Updated 3 years ago
- Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- [NeurIPS 2021] Fast Certified Robust Training with Short Warmup☆24Updated last year
- [ICML'20] Multi Steepest Descent (MSD) for robustness against the union of multiple perturbation models.☆26Updated 9 months ago