Guillaume Leclerc

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 20

Top Topics

Prior Information

Distributed Representations

Top Venues

BrainLes@MICCAI (1)

Publications

Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry
TRAK: Attributing Model Behavior at Scale. CoRR (2023)
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry
Rethinking Backdoor Attacks. CoRR (2023)
Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry
Raising the Cost of Malicious AI-Powered Image Editing. ICML (2023)
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry
Rethinking Backdoor Attacks. ICML (2023)
Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry
FFCV: Accelerating Training by Removing Data Bottlenecks. CVPR (2023)
Hadi Salman, Alaa Khaddaj, Guillaume Leclerc, Andrew Ilyas, Aleksander Madry
Raising the Cost of Malicious AI-Powered Image Editing. CoRR (2023)
Sung Min Park, Kristian Georgiev, Andrew Ilyas, Guillaume Leclerc, Aleksander Madry
TRAK: Attributing Model Behavior at Scale. ICML (2023)
Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry
FFCV: Accelerating Training by Removing Data Bottlenecks. CoRR (2023)
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)
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry
Datamodels: Understanding Predictions with Data and Data with Predictions. ICML (2022)
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)
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 (2022)
Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry
Datamodels: Predicting Predictions from Training Data. CoRR (2022)
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 (2021)
Aditya Saligrama, Guillaume Leclerc
Revisiting Ensembles in an Adversarial Context: Improving Natural Accuracy. CoRR (2020)
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)
Guillaume Leclerc, Aleksander Madry
The Two Regimes of Deep Network Training. CoRR (2020)
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)
Guillaume Leclerc, Manasi Vartak, Raul Castro Fernandez, Tim Kraska, Samuel Madden
Smallify: Learning Network Size while Training. CoRR (2018)
Guillaume Leclerc, Joshua Evan Auerbach, Giovanni Iacca, Dario Floreano
The Seamless Peer and Cloud Evolution Framework. GECCO (2016)