csdongxian / AWP
Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"
☆179Updated 4 years ago
Alternatives and similar repositories for AWP
Users that are interested in AWP are comparing it to the libraries listed below
Sorting:
- Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…☆96Updated 3 years ago
- Empirical tricks for training robust models (ICLR 2021)☆253Updated last year
- [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang☆114Updated 3 years ago
- Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"☆147Updated 4 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 5 years ago
- Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)☆125Updated last year
- A Self-Consistent Robust Error (ICML 2022)☆67Updated last year
- PyTorch Implementation of Adversarial Training for Free!☆246Updated 3 years ago
- A pytorch implementation of "Towards Deep Learning Models Resistant to Adversarial Attacks"☆154Updated 5 years ago
- ☆157Updated 4 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
- Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf☆141Updated 5 years ago
- [ICCV 2019] Enhancing Adversarial Example Transferability with an Intermediate Level Attack (https://arxiv.org/abs/1907.10823)☆78Updated 5 years ago
- [ICLR 2020] A repository for extremely fast adversarial training using FGSM☆443Updated 9 months ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago
- the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral☆59Updated 4 years ago
- PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.☆250Updated 4 years ago
- Understanding and Improving Fast Adversarial Training [NeurIPS 2020]☆95Updated 3 years ago
- ☆107Updated 3 years ago
- Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)☆136Updated last year
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 4 years ago
- Code for the paper "On the Adversarial Robustness of Visual Transformers"☆56Updated 3 years ago
- ☆58Updated 2 years ago
- ☆35Updated 4 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆30Updated 3 years ago
- Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"☆53Updated 4 years ago
- Codes for ICLR 2020 paper "Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets"☆71Updated 4 years ago
- Learnable Boundary Guided Adversarial Training (ICCV2021)☆38Updated 5 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