Quentin Garrido

According to our database, Quentin Garrido authored at least 13 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

An Introduction to Vision-Language Modeling.

Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra

CoRR, 2024

Revisiting Feature Prediction for Learning Visual Representations from Video.

Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas

CoRR, 2024

Learning and Leveraging World Models in Visual Representation Learning.

Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun

CoRR, 2024

UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling.

Haider Al-Tahan, Quentin Garrido, Randall Balestriero, Diane Bouchacourt, Caner Hazirbas, Mark Ibrahim

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

The Robustness Limits of SoTA Vision Models to Natural Variation.

Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt

Trans. Mach. Learn. Res., 2023

Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning.

Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent

Trans. Mach. Learn. Res., 2023

A Cookbook of Self-Supervised Learning.

Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum

CoRR, 2023

Self-Supervised Learning with Lie Symmetries for Partial Differential Equations.

Grégoire Mialon, Quentin Garrido, Hannah Lawrence, Danyal Rehman, Yann LeCun, Bobak T. Kiani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Self-supervised learning of Split Invariant Equivariant representations.

Quentin Garrido, Laurent Najman, Yann LeCun

Proceedings of the International Conference on Machine Learning, 2023

RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank.

Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun

Proceedings of the International Conference on Machine Learning, 2023

On the duality between contrastive and non-contrastive self-supervised learning.

Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, Yann LeCun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head.

Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent

CoRR, 2022

Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder.

Quentin Garrido, Sebastian Damrich, Alexander Jäger, Dario Cerletti, Manfred Claassen, Laurent Najman, Fred A. Hamprecht

Bioinform., 2022