nvedant07 / Fairness-Through-RobustnessLinks
Official code for FAccT'21 paper "Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning" https://arxiv.org/abs/2006.12621
☆13Updated 4 years ago
Alternatives and similar repositories for Fairness-Through-Robustness
Users that are interested in Fairness-Through-Robustness are comparing it to the libraries listed below
Sorting:
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆47Updated 3 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆20Updated 2 years ago
- [CVPR 2022] "Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free" by Tianlong Chen*, Zhenyu Zhang*, Yihua Zhang*, Shiyu C…☆27Updated 3 years ago
- How Robust are Randomized Smoothing based Defenses to Data Poisoning? (CVPR 2021)☆13Updated 4 years ago
- Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks☆39Updated 4 years ago
- Codes for reproducing the results of the paper "Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness" published at IC…☆27Updated 5 years ago
- Code for the paper "Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks"☆13Updated 3 years ago
- Not All Poisons are Created Equal: Robust Training against Data Poisoning (ICML 2022)☆20Updated 3 years ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 6 years ago
- RAB: Provable Robustness Against Backdoor Attacks☆39Updated 2 years ago
- Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off☆33Updated 3 years ago
- [ICLR'21] Dataset Inference for Ownership Resolution in Machine Learning☆32Updated 3 years ago
- Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"☆58Updated 2 years ago
- ☆19Updated 2 years ago
- [NeurIPS'22] Trap and Replace: Defending Backdoor Attacks by Trapping Them into an Easy-to-Replace Subnetwork. Haotao Wang, Junyuan Hong,…☆15Updated last year
- ☆67Updated last year
- [Preprint] On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping☆10Updated 5 years ago
- Code for paper "Poisoned classifiers are not only backdoored, they are fundamentally broken"☆26Updated 3 years ago
- Implementation of Confidence-Calibrated Adversarial Training (CCAT).☆45Updated 5 years ago
- ☆23Updated 2 years ago
- The code is for our NeurIPS 2019 paper: https://arxiv.org/abs/1910.04749☆34Updated 5 years ago
- ☆10Updated 3 years ago
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- Code for "Neuron Shapley: Discovering the Responsible Neurons"☆27Updated last year
- [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…☆39Updated 3 years ago
- Certified Removal from Machine Learning Models☆69Updated 4 years ago
- ☆26Updated 6 years ago
- ConvexPolytopePosioning☆37Updated 5 years ago
- ☆24Updated 2 years ago