| Towards Deep Learning Models Resistant to Adversarial Attacks A Madry, A Makelov, L Schmidt, D Tsipras, A Vladu arXiv preprint arXiv:1706.06083, 2017 | 2896 | 2017 |
| How Does Batch Normalization Help Optimization? S Santurkar, D Tsipras, A Ilyas, A Madry | 579 | 2018 |
| Robustness may be at odds with accuracy D Tsipras, S Santurkar, L Engstrom, A Turner, A Madry arXiv preprint arXiv:1805.12152, 2018 | 521* | 2018 |
| Adversarial examples are not bugs, they are features A Ilyas, S Santurkar, D Tsipras, L Engstrom, B Tran, A Madry Advances in Neural Information Processing Systems, 125-136, 2019 | 452 | 2019 |
| Adversarially robust generalization requires more data L Schmidt, S Santurkar, D Tsipras, K Talwar, A Madry Advances in Neural Information Processing Systems, 5014-5026, 2018 | 315 | 2018 |
| Exploring the Landscape of Spatial Robustness L Engstrom, B Tran, D Tsipras, L Schmidt, A Madry International Conference on Machine Learning, 1802-1811, 2019 | 308* | 2019 |
| On Evaluating Adversarial Robustness N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ... arXiv preprint arXiv:1902.06705, 2019 | 271 | 2019 |
| Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods MB Cohen, A Madry, D Tsipras, A Vladu Foundations of Computer Science (FOCS), 2017 IEEE 58th Annual Symposium on …, 2017 | 67 | 2017 |
| Image Synthesis with a Single (Robust) Classifier S Santurkar, A Ilyas, D Tsipras, L Engstrom, B Tran, A Madry Advances in Neural Information Processing Systems, 1260-1271, 2019 | 55* | 2019 |
| A Closer Look at Deep Policy Gradients A Ilyas, L Engstrom, S Santurkar, D Tsipras, F Janoos, L Rudolph, ... arXiv preprint arXiv:1811.02553, 2018 | 55* | 2018 |
| Adversarial robustness as a prior for learned representations L Engstrom, A Ilyas, S Santurkar, D Tsipras, B Tran, A Madry arXiv preprint arXiv:1906.00945, 2019 | 53* | 2019 |
| Implementation Matters in Deep RL: A Case Study on PPO and TRPO L Engstrom, A Ilyas, S Santurkar, D Tsipras, F Janoos, L Rudolph, ... International Conference on Learning Representations, 2019 | 50* | 2019 |
| Label-Consistent Backdoor Attacks A Turner, D Tsipras, A Madry arXiv preprint arXiv:1912.02771, 2019 | 40* | 2019 |
| Robustness (python library), 2019 L Engstrom, A Ilyas, S Santurkar, D Tsipras URL https://github. com/MadryLab/robustness, 0 | 28 | |
| Identifying statistical bias in dataset replication L Engstrom, A Ilyas, S Santurkar, D Tsipras, J Steinhardt, A Madry International Conference on Machine Learning, 2922-2932, 2020 | 13 | 2020 |
| A Discussion of'Adversarial Examples Are Not Bugs, They Are Features': Discussion and Author Responses L Engstrom, A Ilyas, A Madry, S Santurkar, B Tran, D Tsipras Distill 4 (8), e00019. 7, 2019 | 12 | 2019 |
| From imagenet to image classification: Contextualizing progress on benchmarks D Tsipras, S Santurkar, L Engstrom, A Ilyas, A Madry International Conference on Machine Learning, 9625-9635, 2020 | 7 | 2020 |
| Efficient Money Burning in General Domains D Fotakis, D Tsipras, C Tzamos, E Zampetakis Theory of Computing Systems 59 (4), 619-640, 2016 | 3 | 2016 |
| BREEDS: Benchmarks for Subpopulation Shift S Santurkar, D Tsipras, A Madry arXiv preprint arXiv:2008.04859, 2020 | 2 | 2020 |
| Data Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses M Goldblum, D Tsipras, C Xie, X Chen, A Schwarzschild, D Song, ... arXiv preprint arXiv:2012.10544, 2020 | 1 | 2020 |
Aleksander MądryMITVerified email at mit.edu
