| Scaling vision with sparse mixture of experts C Riquelme, J Puigcerver, B Mustafa, M Neumann, R Jenatton, ... Advances in Neural Information Processing Systems 34, 8583-8595, 2021 | 562 | 2021 |
| A large-scale study of representation learning with the visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 388 | 2019 |
| Paligemma: A versatile 3b vlm for transfer L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... arXiv preprint arXiv:2407.07726, 2024 | 119 | 2024 |
| The visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... | 79 | 2019 |
| Uvim: A unified modeling approach for vision with learned guiding codes A Kolesnikov, A Susano Pinto, L Beyer, X Zhai, J Harmsen, N Houlsby Advances in Neural Information Processing Systems 35, 26295-26308, 2022 | 74 | 2022 |
| In-domain representation learning for remote sensing M Neumann, AS Pinto, X Zhai, N Houlsby arXiv preprint arXiv:1911.06721, 2019 | 73 | 2019 |
| Learning to merge tokens in vision transformers C Renggli, AS Pinto, N Houlsby, B Mustafa, J Puigcerver, C Riquelme arXiv preprint arXiv:2202.12015, 2022 | 72 | 2022 |
| Scalable transfer learning with expert models J Puigcerver, C Riquelme, B Mustafa, C Renggli, AS Pinto, S Gelly, ... arXiv preprint arXiv:2009.13239, 2020 | 65 | 2020 |
| Tuning computer vision models with task rewards AS Pinto, A Kolesnikov, Y Shi, L Beyer, X Zhai International Conference on Machine Learning, 33229-33239, 2023 | 42 | 2023 |
| Scaling vision with sparse mixture of experts CR Ruiz, J Puigcerver, B Mustafa, M Neumann, R Jenatton, AS Pinto, ... Advances in Neural Information Processing Systems, 2021 | 32 | 2021 |
| Which model to transfer? finding the needle in the growing haystack C Renggli, AS Pinto, L Rimanic, J Puigcerver, C Riquelme, C Zhang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 22 | 2022 |
| Deep ensembles for low-data transfer learning B Mustafa, C Riquelme, J Puigcerver, AS Pinto, D Keysers, N Houlsby arXiv preprint arXiv:2010.06866, 2020 | 22 | 2020 |
| Training general representations for remote sensing using in-domain knowledge M Neumann, AS Pinto, X Zhai, N Houlsby IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 19 | 2020 |
| A study of autoregressive decoders for multi-tasking in computer vision L Beyer, B Wan, G Madan, F Pavetic, A Steiner, A Kolesnikov, AS Pinto, ... arXiv preprint arXiv:2303.17376, 2023 | 8 | 2023 |
| Adaptive Collapsing on Bounding Volume Hierarchies for Ray-Tracing A Susano Pinto | 7* | 2010 |
| Novelty detection using graphical models for semantic room classification A Susano Pinto, A Pronobis, L Reis Progress in Artificial Intelligence, 326-339, 2011 | 5* | 2011 |
| LocCa: Visual Pretraining with Location-aware Captioners B Wan, M Tschannen, Y Xian, F Pavetic, I Alabdulmohsin, X Wang, ... arXiv preprint arXiv:2403.19596, 2024 | 3 | 2024 |
| PaliGemma 2: A Family of Versatile VLMs for Transfer A Steiner, AS Pinto, M Tschannen, D Keysers, X Wang, Y Bitton, ... arXiv preprint arXiv:2412.03555, 2024 | 1 | 2024 |
| JetFormer: An autoregressive generative model of raw images and text M Tschannen, AS Pinto, A Kolesnikov arXiv preprint arXiv:2411.19722, 2024 | 1 | 2024 |
| Jet: A Modern Transformer-Based Normalizing Flow A Kolesnikov, AS Pinto, M Tschannen arXiv preprint arXiv:2412.15129, 2024 | | 2024 |
Neil HoulsbyGoogle在 google.com 的电子邮件经过验证