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Guillaume Leclerc
Guillaume Leclerc
PhD Student
Verified email at mit.edu
Title
Cited by
Cited by
Year
Sagedb: A learned database system
T Kraska, M Alizadeh, A Beutel, EH Chi, J Ding, A Kristo, G Leclerc, ...
2082021
Datamodels: Predicting predictions from training data
A Ilyas, SM Park, L Engstrom, G Leclerc, A Madry
arXiv preprint arXiv:2202.00622, 2022
832022
Raising the cost of malicious ai-powered image editing
H Salman, A Khaddaj, G Leclerc, A Ilyas, A Madry
arXiv preprint arXiv:2302.06588, 2023
552023
Trak: Attributing model behavior at scale
SM Park, K Georgiev, A Ilyas, G Leclerc, A Madry
arXiv preprint arXiv:2303.14186, 2023
542023
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
452022
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
402023
Adversarially trained neural representations are already as robust as biological neural representations
C Guo, M Lee, G Leclerc, J Dapello, Y Rao, A Madry, J Dicarlo
International Conference on Machine Learning, 8072-8081, 2022
372022
The two regimes of deep network training
G Leclerc, A Madry
arXiv preprint arXiv:2002.10376, 2020
362020
Datamodels: Understanding predictions with data and data with predictions
A Ilyas, SM Park, L Engstrom, G Leclerc, A Madry
International Conference on Machine Learning, 9525-9587, 2022
232022
The seamless peer and cloud evolution framework
G Leclerc, JE Auerbach, G Iacca, D Floreano
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 821-828, 2016
202016
Smallify: Learning network size while training
G Leclerc, M Vartak, RC Fernandez, T Kraska, S Madden
arXiv preprint arXiv:1806.03723, 2018
172018
Model metamers reveal divergent invariances between biological and artificial neural networks
J Feather, G Leclerc, A Mądry, JH McDermott
Nature Neuroscience 26 (11), 2017-2034, 2023
102023
Model metamers illuminate divergences between biological and artificial neural networks
J Feather, G Leclerc, A Mądry, JH McDermott
bioRxiv, 2022.05. 19.492678, 2022
102022
Madry, A. ffcv
G Leclerc, A Ilyas, L Engstrom, SM Park, H Salman
82022
Rethinking backdoor attacks
A Khaddaj, G Leclerc, A Makelov, K Georgiev, H Salman, A Ilyas, A Madry
International Conference on Machine Learning, 16216-16236, 2023
62023
Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions
J Klug, G Leclerc, E Dirren, MG Preti, D Van De Ville, E Carrera
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021
22021
Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy
A Saligrama, G Leclerc
arXiv preprint arXiv:2002.11572, 2020
22020
Learning network size while training with ShrinkNets
G Leclerc, RC Fernandez, S Madden
Conference on Systems and Machine Learning, 2018
22018
Extra Training Provides a Strong Baseline for CLIP
A Khaddaj, H Salman, A Ilyas, G Leclerc, A Madry
R0-FoMo: Robustness of Few-shot and Zero-shot Learning in Large Foundation …, 2023
2023
Your CLIP Model Might Be Undertrained
A Khaddaj, H Salman, A Ilyas, G Leclerc, A Madry
2023
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