| Vicreg: Variance-invariance-covariance regularization for self-supervised learning A Bardes, J Ponce, Y LeCun International Conference on Learning Representations (ICLR), 2021 | 1070 | 2021 |
| VICRegL: Self-Supervised Learning of Local Visual Features A Bardes, J Ponce, Y LeCun Neural Information Processing Systems (NeurIPS), 2022 | 87 | 2022 |
| On the duality between contrastive and non-contrastive self-supervised learning Q Garrido, Y Chen, A Bardes, L Najman, Y Lecun International Conference on Learning Representations (ICLR), 2022 | 79 | 2022 |
| A cookbook of self-supervised learning R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ... International Conference on Machine Learning (ICML Tutorials), 2023 | 49* | 2023 |
| Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning F Bordes, R Balestriero, Q Garrido, A Bardes, P Vincent Transactions on Machine Learning Research (TMLR), 2023 | 31* | 2023 |
| Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks M Goldblum, H Souri, R Ni, M Shu, V Prabhu, G Somepalli, ... Neural Information Processing Systems (NeurIPS), 2023 | 22 | 2023 |
| Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning Y Chen, A Bardes, Z Li, Y LeCun Transactions on Machine Learning Research (TMLR), 2022 | 13* | 2022 |
| Mc-jepa: A joint-embedding predictive architecture for self-supervised learning of motion and content features A Bardes, J Ponce, Y LeCun arXiv preprint arXiv:2307.12698, 2023 | 12 | 2023 |
| Learning To Hallucinate Examples From Extrinsic and Intrinsic Supervision L Gui, A Bardes, R Salakhutdinov, A Hauptmann, M Hebert, YX Wang International Conference on Computer Vision (ICCV), 2021 | 7 | 2021 |
| No Free Lunch in Self Supervised Representation Learning I Bendidi, A Bardes, E Cohen, A Lamiable, G Bollot, A Genovesio Self-Supervised Learning (NeurIPS Workshop), 2023 | 6 | 2023 |
| V-jepa: Latent video prediction for visual representation learning A Bardes, Q Garrido, J Ponce, X Chen, M Rabbat, Y LeCun, M Assran, ... | 5 | 2023 |
| 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 | 4 | 2024 |
| 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 |
| Progressive Knowledge Distillation For Generative Modeling A Bardes, YX Wang, R Salakhutdinov, M Hebert Learning with Rich Experience (NeurIPS workshop), 2019 | 2* | 2019 |
| VICRegL: Self-Supervised Learning of Local Visual A Bardes, J Ponce, Y LeCun | | |
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York University在 cs.nyu.edu 的电子邮件经过验证
