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ORCIDGuillaume Leclerc
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2020 – today
- 2024
[b1]Guillaume Leclerc:
Robust Computer Vision beyond Lₚ Adversaries. MIT, USA, 2024- 2023
- [c10]Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry:
FFCV: Accelerating Training by Removing Data Bottlenecks. CVPR 2023: 12011-12020 - [c9]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. ICML 2023: 16216-16236 - [c8]Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. ICML 2023: 27074-27113 - [c7]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. ICML 2023: 29894-29918 - [i10]Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry:
Raising the Cost of Malicious AI-Powered Image Editing. CoRR abs/2302.06588 (2023) - [i9]Sung Min Park, Kristian Georgiev
, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry:
TRAK: Attributing Model Behavior at Scale. CoRR abs/2303.14186 (2023) - [i8]Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry:
FFCV: Accelerating Training by Removing Data Bottlenecks. CoRR abs/2306.12517 (2023) - [i7]Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry:
Rethinking Backdoor Attacks. CoRR abs/2307.10163 (2023) - 2022
- [c6]Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James J. DiCarlo:
Adversarially trained neural representations are already as robust as biological neural representations. ICML 2022: 8072-8081 - [c5]Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry:
Datamodels: Understanding Predictions with Data and Data with Predictions. ICML 2022: 9525-9587 - [c4]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. NeurIPS 2022 - [i6]Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry:
Datamodels: Predicting Predictions from Training Data. CoRR abs/2202.00622 (2022) - [i5]Chong Guo, Michael J. Lee, Guillaume Leclerc, Joel Dapello, Yug Rao, Aleksander Madry, James J. DiCarlo:
Adversarially trained neural representations may already be as robust as corresponding biological neural representations. CoRR abs/2206.11228 (2022) - 2021
- [i4]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. CoRR abs/2106.03805 (2021) - 2020
- [c3]Julian Klug, Guillaume Leclerc, Elisabeth Dirren, Maria Giulia Preti, Dimitri Van De Ville, Emmanuel Carrera:
Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions. BrainLes@MICCAI (1) 2020: 168-180 - [i3]Guillaume Leclerc, Aleksander Madry:
The Two Regimes of Deep Network Training. CoRR abs/2002.10376 (2020) - [i2]Aditya Saligrama, Guillaume Leclerc:
Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy. CoRR abs/2002.11572 (2020)
2010 – 2019
- 2019
- [c2]Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan:
SageDB: A Learned Database System. CIDR 2019 - 2018
- [i1]Guillaume Leclerc, Manasi Vartak, Raul Castro Fernandez, Tim Kraska, Samuel Madden:
Smallify: Learning Network Size while Training. CoRR abs/1806.03723 (2018) - 2016
- [c1]Guillaume Leclerc, Joshua Evan Auerbach, Giovanni Iacca, Dario Floreano:
The Seamless Peer and Cloud Evolution Framework. GECCO 2016: 821-828
Coauthor Index
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last updated on 2024-08-29 20:58 CEST by the dblp team
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