hammlab / LimitsOfUDA
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning. (Neurips 2021)
☆8Updated 3 years ago
Alternatives and similar repositories for LimitsOfUDA:
Users that are interested in LimitsOfUDA are comparing it to the libraries listed below
- [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning☆30Updated last year
- 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 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 <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.☆12Updated 2 years ago
- [NeurIPS 2022] "Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets" by Ruisi Cai*, Zhenyu Zh…☆20Updated 2 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 years ago
- [NeurIPS'22] Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. Haotao Wang, Junyuan Hong,…☆14Updated last year
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆38Updated 3 years ago
- Code for the paper "SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness" (NeurIPS 2021)☆21Updated 2 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
- [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
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- ☆11Updated 2 years ago
- ☆22Updated 2 years ago
- 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
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 5 years ago
- RAB: Provable Robustness Against Backdoor Attacks☆39Updated last year
- ☆19Updated 3 years ago
- Certified Patch Robustness via Smoothed Vision Transformers☆42Updated 3 years ago
- SEAT☆20Updated last year
- Code for "Neuron Shapley: Discovering the Responsible Neurons"☆25Updated 10 months ago
- [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training☆31Updated 3 years ago
- Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆20Updated 11 months ago
- This is the code for semi-supervised robust training (SRT).☆18Updated 2 years ago
- [NeurIPS 2020] code for "Boundary thickness and robustness in learning models"☆19Updated 4 years ago
- ☆10Updated 3 years ago
- [ICLR 2022] Boosting Randomized Smoothing with Variance Reduced Classifiers☆12Updated 2 years ago
- Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]☆52Updated 2 years ago
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆29Updated 2 years ago