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Guillaume Leclerc · SciRah

Researcher profile · Semantic Scholar

Guillaume Leclerc

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Guillaume Leclerc — researcher profile on SciRah

h-index: 14
Works: 20
Citations: 1,539

Most-cited papers

TRAK: Attributing Model Behavior at Scale
Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc +1 more
2023International Conference on Machine Learning367 citations Open access
Semantic Scholar
Raising the Cost of Malicious AI-Powered Image Editing
Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas +1 more
2023International Conference on Machine Learning238 citations Open access
Semantic Scholar
Datamodels: Predicting Predictions from Training Data
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc +1 more
2022arXiv.org232 citations
Semantic Scholar
SageDB: A Learned Database System
Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi +6 more
2019Conference on Innovative Data Systems Research208 citations
Semantic Scholar
Datamodels: Understanding Predictions with Data and Data with Predictions
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc +1 more
2022International Conference on Machine Learning106 citations
Semantic Scholar
FFCV: Accelerating Training by Removing Data Bottlenecks
Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park +2 more
2023Computer Vision and Pattern Recognition93 citations Open access
Semantic Scholar
Model metamers reveal divergent invariances between biological and artificial neural networks
J. Feather, Guillaume Leclerc, Aleksander Madry, Josh H. McDermott
2023Nature Neuroscience69 citations Open access
Semantic Scholar
The Two Regimes of Deep Network Training
Guillaume Leclerc, A. Ma̧dry
2020arXiv.org53 citations
Semantic Scholar
3DB: A Framework for Debugging Computer Vision Models
Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai H. Vemprala +8 more
2021Neural Information Processing Systems45 citations
Semantic Scholar
Rethinking Backdoor Attacks
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev +3 more
2023International Conference on Machine Learning43 citations Open access
Semantic Scholar
Adversarially trained neural representations are already as robust as biological neural representations
Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello +3 more
2022International Conference on Machine Learning31 citations
Semantic Scholar
Adversarially trained neural representations may already be as robust as corresponding biological neural representations
Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello +3 more
2022arXiv.org21 citations Open access
Semantic Scholar
Model metamers illuminate divergences between biological and artificial neural networks
J. Feather, Guillaume Leclerc, A. Ma̧dry, Josh H. McDermott
2023bioRxiv19 citations Open access
Semantic Scholar
The Seamless Peer and Cloud Evolution Framework
Guillaume Leclerc, J. E. Auerbach, Giovanni Iacca, D. Floreano
2016Annual Conference on Genetic and Evolutionary Computation19 citations Open access
Semantic Scholar
Smallify: Learning Network Size while Training
Guillaume Leclerc, Manasi Vartak, R. Fernandez, Tim Kraska +1 more
2018arXiv.org13 citations
Semantic Scholar
Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions
Julian Klug, Guillaume Leclerc, Elisabeth Dirren, M. Preti +2 more
2020BrainLes@MICCAI2 citations Open access
Semantic Scholar
Learning Network Size While Training with ShrinkNets
Guillaume Leclerc, R. Fernandez, Samuel Madden
20182 citations
Semantic Scholar
Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy
Aditya Saligrama, Guillaume Leclerc
2020arXiv.org1 citations
Semantic Scholar
Abstract P357: Deep Learning Building on Prior Ischemic Core Segmentation Improves Prediction of Infarction After Stroke
Julian Klug, Guillaume Leclerc, Elisabeth Dirren, Preti Maria Gulia +2 more
2021Stroke0 citations Open access
Semantic Scholar
Exploration of Capabilities and Limitations in View Change of the X-Fields Model
J. Wang, Guillaume Leclerc
0 citations
Semantic Scholar

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