ChaojianYu / Understanding-Robust-Overfitting
Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.
☆12Updated 2 years ago
Alternatives and similar repositories for Understanding-Robust-Overfitting:
Users that are interested in Understanding-Robust-Overfitting are comparing it to the libraries listed below
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆29Updated 2 years ago
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆27Updated 4 years ago
- the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral☆59Updated 3 years ago
- [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning☆30Updated last year
- [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training☆31Updated 3 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 5 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
- Implementation for <Robust Weight Perturbation for Adversarial Training> in IJCAI'22.☆14Updated 2 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- ☆10Updated 3 years ago
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆38Updated 3 years ago
- Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation (NeurIPS 2022)☆33Updated 2 years ago
- [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks☆34Updated 8 months ago
- Code for the CVPR 2020 article "Adversarial Vertex mixup: Toward Better Adversarially Robust Generalization"☆13Updated 4 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
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆52Updated 2 years ago
- SEAT☆20Updated last year
- Code for the paper "Autoregressive Perturbations for Data Poisoning" (NeurIPS 2022)☆20Updated 6 months ago
- ☆21Updated 3 years ago
- Learnable Boundary Guided Adversarial Training (ICCV2021)☆37Updated 3 months ago
- Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)☆16Updated 2 years ago
- Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning. (Neurips 2021)☆8Updated 3 years ago
- ☆11Updated 2 years ago
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Updated 3 years ago
- Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.☆42Updated 2 years ago
- ☆29Updated 3 years ago
- kyleliang919 / Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferabilitycode for ICML 2021 paper in which we explore the relationship between adversarial transferability and knowledge transferability.☆17Updated 2 years ago
- Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…☆95Updated 3 years ago
- [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers☆21Updated 3 years ago
- ☆20Updated 2 weeks ago