nmndeep / revisiting-atLinks
[NeurIPS 2023] Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models"
☆37Updated 9 months ago
Alternatives and similar repositories for revisiting-at
Users that are interested in revisiting-at are comparing it to the libraries listed below
Sorting:
- Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)☆143Updated 2 years ago
- Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…☆97Updated 3 years ago
- Towards Efficient and Effective Adversarial Training, NeurIPS 2021☆17Updated 3 years ago
- Code for the paper "On the Adversarial Robustness of Visual Transformers"☆58Updated 3 years ago
- Certified robustness "for free" using off-the-shelf diffusion models and classifiers☆43Updated 2 years ago
- the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral☆59Updated 4 years ago
- ☆35Updated 2 years ago
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆53Updated 2 years ago
- ☆54Updated 4 years ago
- Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation (NeurIPS 2022)☆33Updated 2 years ago
- A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)☆31Updated 3 years ago
- [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers☆21Updated 3 years ago
- ☆22Updated 4 years ago
- Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"☆151Updated 4 years ago
- ☆53Updated 2 years ago
- PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM☆25Updated 5 years ago
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆16Updated 2 years ago
- Code for the paper "Autoregressive Perturbations for Data Poisoning" (NeurIPS 2022)☆20Updated last year
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Updated 3 years ago
- APBench: A Unified Availability Poisoning Attack and Defenses Benchmark (TMLR 08/2024)☆35Updated 5 months ago
- ☆23Updated last year
- ☆23Updated 2 years ago
- ☆59Updated 2 years ago
- Revisiting Transferable Adversarial Images (arXiv)☆129Updated 6 months ago
- Implementation of "Adversarial purification with Score-based generative models", ICML 2021☆29Updated 3 years ago
- [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning☆31Updated last year
- Code for Transferable Unlearnable Examples☆20Updated 2 years ago
- Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.☆12Updated 3 years ago
- ☆20Updated 6 months ago
- ATTA (Efficient Adversarial Training with Transferable Adversarial Examples)☆36Updated 5 years ago