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Logan Engstrom
Logan Engstrom
Verified email at mit.edu - Homepage
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Year
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 32, 2019
19062019
Robustness may be at odds with accuracy
D Tsipras, S Santurkar, L Engstrom, A Turner, A Madry
arXiv preprint arXiv:1805.12152, 2018
18582018
Synthesizing robust adversarial examples
A Athalye, L Engstrom, A Ilyas, K Kwok
arXiv preprint arXiv:1707.07397, 2017
18142017
Black-box adversarial attacks with limited queries and information
A Ilyas, L Engstrom, A Athalye, J Lin
International conference on machine learning, 2137-2146, 2018
13162018
A rotation and a translation suffice: Fooling cnns with simple transformations
L Engstrom, B Tran, D Tsipras, L Schmidt, A Madry
843*2018
Do adversarially robust imagenet models transfer better?
H Salman, A Ilyas, L Engstrom, A Kapoor, A Madry
Advances in Neural Information Processing Systems 33, 3533-3545, 2020
4112020
Prior convictions: Black-box adversarial attacks with bandits and priors
A Ilyas, L Engstrom, A Madry
arXiv preprint arXiv:1807.07978, 2018
4082018
Implementation matters in deep policy gradients: A case study on ppo and trpo
L Engstrom, A Ilyas, S Santurkar, D Tsipras, F Janoos, L Rudolph, ...
arXiv preprint arXiv:2005.12729, 2020
3422020
Noise or signal: The role of image backgrounds in object recognition
K Xiao, L Engstrom, A Ilyas, A Madry
arXiv preprint arXiv:2006.09994, 2020
3352020
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
246*2019
Computer vision with a single (robust) classifier
S Santurkar, D Tsipras, B Tran, A Ilyas, L Engstrom, A Madry
arXiv preprint arXiv:1906.09453 4, 1, 2019
218*2019
Robustness (python library), 2019
L Engstrom, A Ilyas, H Salman, S Santurkar, D Tsipras
URL https://github. com/MadryLab/robustness 4 (4), 4.3, 2019
2012019
Evaluating and understanding the robustness of adversarial logit pairing
L Engstrom, A Ilyas, A Athalye
arXiv preprint arXiv:1807.10272, 2018
1472018
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
1462020
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
133*2018
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
1232019
Datamodels: Predicting predictions from training data
A Ilyas, SM Park, L Engstrom, G Leclerc, A Madry
arXiv preprint arXiv:2202.00622, 2022
782022
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
552020
Unadversarial examples: Designing objects for robust vision
H Salman, A Ilyas, L Engstrom, S Vemprala, A Madry, A Kapoor
Advances in Neural Information Processing Systems 34, 15270-15284, 2021
462021
3db: A framework for debugging computer vision models
G Leclerc, H Salman, A Ilyas, S Vemprala, L Engstrom, V Vineet, K Xiao, ...
Advances in Neural Information Processing Systems 35, 8498-8511, 2022
442022
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