kyleliang919 / Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferability
code for ICML 2021 paper in which we explore the relationship between adversarial transferability and knowledge transferability.
☆17Updated 2 years ago
Alternatives and similar repositories for Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferability:
Users that are interested in Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferability are comparing it to the libraries listed below
- Implementation of our ICLR 2021 paper: Policy-Driven Attack: Learning to Query for Hard-label Black-box Adversarial Examples.☆11Updated 3 years ago
- ☆22Updated 2 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 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
- Codes for reproducing the results of the paper "Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness" published at IC…☆26Updated 4 years ago
- Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.☆12Updated 2 years ago
- [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks☆34Updated 6 months ago
- ☆35Updated 4 years ago
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆38Updated 3 years ago
- [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training☆31Updated 3 years ago
- Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020☆26Updated 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
- Repository for Knowledge Enhanced Machine Learning Pipeline (KEMLP)☆10Updated 3 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 2 years ago
- [NeurIPS 2022] "Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets" by Ruisi Cai*, Zhenyu Zh…☆19Updated 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 for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019☆47Updated 2 years ago
- ☆29Updated 2 years ago
- Code for paper "Poisoned classifiers are not only backdoored, they are fundamentally broken"☆26Updated 3 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 "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆19Updated 9 months ago
- Code for the paper titled "Adversarial Vulnerability of Randomized Ensembles" (ICML 2022).☆10Updated 2 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 5 years ago
- ☆10Updated 3 years ago
- Pytorch implementation of NPAttack☆12Updated 4 years ago
- ☆14Updated 5 years ago
- ☆16Updated 5 years ago
- MACER: MAximizing CErtified Radius (ICLR 2020)☆28Updated 5 years ago
- ☆53Updated last year
- Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning. (Neurips 2021)☆8Updated 3 years ago