Seguir
Logan Engstrom
Logan Engstrom
MIT
Dirección de correo verificada de mit.edu - Página principal
Título
Citado por
Citado por
Año
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
21402019
Robustness may be at odds with accuracy
D Tsipras, S Santurkar, L Engstrom, A Turner, A Madry
arXiv preprint arXiv:1805.12152, 2018
20572018
Synthesizing robust adversarial examples
A Athalye, L Engstrom, A Ilyas, K Kwok
arXiv preprint arXiv:1707.07397, 2017
20302017
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
14582018
A rotation and a translation suffice: Fooling cnns with simple transformations
L Engstrom, B Tran, D Tsipras, L Schmidt, A Madry
906*2017
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
4732020
Prior convictions: Black-box adversarial attacks with bandits and priors
A Ilyas, L Engstrom, A Madry
arXiv preprint arXiv:1807.07978, 2018
4462018
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
3992020
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
3072019
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
266*2019
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
2642020
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
235*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
2332019
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
1662020
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
157*2018
Evaluating and understanding the robustness of adversarial logit pairing
L Engstrom, A Ilyas, A Athalye
arXiv preprint arXiv:1807.10272, 2018
1512018
Datamodels: Predicting predictions from training data
A Ilyas, SM Park, L Engstrom, G Leclerc, A Madry
arXiv preprint arXiv:2202.00622, 2022
1312022
FFCV: Accelerating training by removing data bottlenecks
G Leclerc, A Ilyas, L Engstrom, SM Park, H Salman, A Mądry
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
642023
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
612020
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
542021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20