erichson / NoisyMixLinks
☆13Updated 3 years ago
Alternatives and similar repositories for NoisyMix
Users that are interested in NoisyMix are comparing it to the libraries listed below
Sorting:
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆33Updated 3 years ago
- CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection☆20Updated 3 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 6 years ago
- Official repository for "On Improving Adversarial Transferability of Vision Transformers" (ICLR 2022--Spotlight)☆72Updated 2 years ago
- Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, N…☆75Updated last year
- This is the official implementation of ClusTR: Clustering Training for Robustness paper.☆20Updated 3 years ago
- A pytorch re-implementation for paper "Towards Deep Learning Models Resistant to Adversarial Attacks"☆19Updated 6 years ago
- Learnable Boundary Guided Adversarial Training (ICCV2021)☆38Updated 8 months ago
- Removing Adversarial Noise in Class Activation Feature Space☆14Updated last year
- Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective☆20Updated last year
- PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM☆25Updated 5 years ago
- [CVPR 2024] This repository includes the official implementation our paper "Revisiting Adversarial Training at Scale"☆20Updated last year
- ☆58Updated 3 years ago
- A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)☆31Updated 3 years ago
- Implementation of "Adversarial purification with Score-based generative models", ICML 2021☆29Updated 3 years ago
- Coupling rejection strategy against adversarial attacks (CVPR 2022)☆29Updated 3 years ago
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆16Updated 2 years ago
- ☆22Updated 3 years ago
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆33Updated 11 months ago
- Triangle Attack: A Query-efficient Decision-based Adversarial Attack (ECCV 2022)☆17Updated 3 years ago
- Understanding Catastrophic Overfitting in Single-step Adversarial Training [AAAI 2021]☆28Updated 3 years ago
- [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"☆45Updated 3 years ago
- Official implementation of "Removing Batch Normalization Boosts Adversarial Training" (ICML'22)☆19Updated 3 years ago
- SEAT☆21Updated last year
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- A Self-Consistent Robust Error (ICML 2022)☆68Updated 2 years ago
- Testing a model performance for CIFAR10-C☆35Updated 5 years ago
- ☆11Updated 3 years ago
- Decoupled Kullback-Leibler Divergence Loss (DKL), NeurIPS 2024 / Generalized Kullback-Leibler Divergence Loss (GKL)☆45Updated last month
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆47Updated 3 years ago