| On the duality between contrastive and non-contrastive self-supervised learning Q Garrido, Y Chen, A Bardes, L Najman, Y Lecun arXiv preprint arXiv:2206.02574, 2022 | 79 | 2022 |
| Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, and Micah Goldblum R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ... A cookbook of self-supervised learning 2, 2023 | 57* | 2023 |
| Rankme: Assessing the downstream performance of pretrained self-supervised representations by their rank Q Garrido, R Balestriero, L Najman, Y Lecun International conference on machine learning, 10929-10974, 2023 | 47 | 2023 |
| Guillotine regularization: Improving deep networks generalization by removing their head F Bordes, R Balestriero, Q Garrido, A Bardes, P Vincent arXiv preprint arXiv:2206.13378 13, 2022 | 31* | 2022 |
| Self-supervised learning of Split Invariant Equivariant representations Q Garrido, L Najman, Y Lecun International Conference on Machine Learning, 10975-10996, 2023 | 20 | 2023 |
| The robustness limits of sota vision models to natural variation M Ibrahim, Q Garrido, A Morcos, D Bouchacourt arXiv preprint arXiv:2210.13604, 2022 | 12 | 2022 |
| Revisiting feature prediction for learning visual representations from video A Bardes, Q Garrido, J Ponce, X Chen, M Rabbat, Y LeCun, M Assran, ... arXiv preprint arXiv:2404.08471, 2024 | 9* | 2024 |
| Self-supervised learning with lie symmetries for partial differential equations G Mialon, Q Garrido, H Lawrence, D Rehman, Y LeCun, B Kiani Advances in Neural Information Processing Systems 36, 28973-29004, 2023 | 6 | 2023 |
| A Cookbook of Self-Supervised Learning. arXiv. Cornell University. April 24, 2023 R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ... arXiv preprint arXiv:2304.12210, 0 | 5 | |
| Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder Q Garrido, S Damrich, A Jäger, D Cerletti, M Claassen, L Najman, ... Bioinformatics 38 (Supplement_1), i316-i324, 2022 | 3 | 2022 |
| An introduction to vision-language modeling F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk, O Mañas, Z Lin, ... arXiv preprint arXiv:2405.17247, 2024 | 2 | 2024 |
| Learning and leveraging world models in visual representation learning Q Garrido, M Assran, N Ballas, A Bardes, L Najman, Y LeCun arXiv preprint arXiv:2403.00504, 2024 | 2 | 2024 |
| Scaling Vision-Language Models Does Not Improve Relational Understanding: The Right Learning Objective Helps H Al-Tahan, Q Garrido, R Balestriero, D Bouchacourt, C Hazirbas, ... | | |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
