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)

Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head. - Florian Bordes; Randall Balestriero; Quentin Garrido; Adrien Bardes; Pascal Vincent (CoRR, 2022)

On the duality between contrastive and non-contrastive self-supervised learning. - Quentin Garrido; Yubei Chen; Adrien Bardes; Laurent Najman; Yann LeCun (ICLR, 2023)

RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank. - Quentin Garrido; Randall Balestriero; Laurent Najman; Yann LeCun (ICML, 2023)

Self-supervised learning of Split Invariant Equivariant representations. - Quentin Garrido; Laurent Najman; Yann LeCun (ICML, 2023)

Self-Supervised Learning with Lie Symmetries for Partial Differential Equations. - Grégoire Mialon; Quentin Garrido; Hannah Lawrence; Danyal Rehman; Yann LeCun; Bobak T. Kiani (NeurIPS, 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; et al. (CoRR, 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)

The Robustness Limits of SoTA Vision Models to Natural Variation. - Mark Ibrahim; Quentin Garrido; Ari S. Morcos; Diane Bouchacourt (Trans. Mach. Learn. Res., 2023)

UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling. - Haider Al-Tahan; Quentin Garrido; Randall Balestriero; Diane Bouchacourt; Caner Hazirbas; Mark Ibrahim (NeurIPS, 2024)

Learning and Leveraging World Models in Visual Representation Learning. - Quentin Garrido; Mahmoud Assran; Nicolas Ballas; Adrien Bardes; Laurent Najman; Yann LeCun (CoRR, 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 002; Bargav Jayaraman; Mark Ibrahim; Melissa Hall; et al. (CoRR, 2024)

Revisiting Feature Prediction for Learning Visual Representations from Video. - Adrien Bardes; Quentin Garrido; Jean Ponce; Xinlei Chen; Michael Rabbat; Yann LeCun; Mido Assran; Nicolas Ballas (Trans. Mach. Learn. Res., 2024)

Intuitive physics understanding emerges from self-supervised pretraining on natural videos. - Quentin Garrido; Nicolas Ballas; Mahmoud Assran; Adrien Bardes; Laurent Najman; Michael Rabbat; Emmanuel Dupoux; Yann LeCun (CoRR, 2025)

IntPhys 2: Benchmarking Intuitive Physics Understanding In Complex Synthetic Environments. - Florian Bordes; Quentin Garrido; Justine T. Kao; Adina Williams; Michael Rabbat; Emmanuel Dupoux (CoRR, 2025)

V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning. - Mido Assran; Adrien Bardes; David Fan; Quentin Garrido; Russell Howes; Mojtaba Komeili; Matthew J. Muckley; Ammar Rizvi; Claire Roberts; Koustuv Sinha; Artem Zholus; Sergio Arnaud; et al. (CoRR, 2025)

A Shortcut-aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs. - Benno Krojer; Mojtaba Komeili; Candace Ross; Quentin Garrido; Koustuv Sinha; Nicolas Ballas; Mahmoud Assran (CoRR, 2025)