Bai-YT / AdaptiveSmoothing
Implementation of the paper "Improving the Accuracy-Robustness Trade-off of Classifiers via Adaptive Smoothing".
☆11Updated last year
Alternatives and similar repositories for AdaptiveSmoothing:
Users that are interested in AdaptiveSmoothing are comparing it to the libraries listed below
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Updated 2 years ago
- Certified robustness "for free" using off-the-shelf diffusion models and classifiers☆37Updated last year
- [CVPR 2024] This repository includes the official implementation our paper "Revisiting Adversarial Training at Scale"☆18Updated 9 months ago
- ☆53Updated last year
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆53Updated 2 years ago
- ☆13Updated 2 years ago
- [CVPR 2022] "Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free" by Tianlong Chen*, Zhenyu Zhang*, Yihua Zhang*, Shiyu C…☆26Updated 2 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆18Updated 2 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- ICLR 2023 paper "Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness" by Yuancheng Xu, Yanchao Sun, Micah Gold…☆24Updated last year
- Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆20Updated 10 months ago
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆29Updated 2 years ago
- Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.☆12Updated 2 years ago
- Certified Patch Robustness via Smoothed Vision Transformers☆42Updated 3 years ago
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆16Updated last year
- ☆34Updated last year
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆26Updated 4 years ago
- Code for the paper "Autoregressive Perturbations for Data Poisoning" (NeurIPS 2022)☆19Updated 5 months ago
- ☆18Updated last year
- Code for paper "Universal Jailbreak Backdoors from Poisoned Human Feedback"☆46Updated 9 months ago
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆30Updated 5 months ago
- [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning☆30Updated last year
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 years ago
- Robustify Black-Box Models (ICLR'22 - Spotlight)☆24Updated 2 years ago
- OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift. ICML 2024 and ICLRW-DMLR 2024☆19Updated 6 months ago
- A Self-Consistent Robust Error (ICML 2022)☆67Updated last year
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- Code for the paper Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation (CVPR 2023).☆34Updated last year
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆46Updated 3 years ago
- ☆17Updated 2 months ago