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| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 2488 | 2023 |
| Learning to navigate in complex environments P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ... arXiv preprint arXiv:1611.03673, 2016 | 1038 | 2016 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 975 | 2024 |
| Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018 | 794 | 2018 |
| Neural scene representation and rendering SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ... Science 360 (6394), 1204-1210, 2018 | 752 | 2018 |
| Neural processes M Garnelo, J Schwarz, D Rosenbaum, F Viola, DJ Rezende, SM Eslami, ... arXiv preprint arXiv:1807.01622, 2018 | 673 | 2018 |
| Gemini: A family of highly capable multimodal models R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805 1, 2023 | 306 | 2023 |
| Taming vaes DJ Rezende, F Viola arXiv preprint arXiv:1810.00597, 2018 | 216 | 2018 |
| The kinetics human action video dataset. arXiv 2017 W Kay, J Carreira, K Simonyan, B Zhang, C Hillier, S Vijayanarasimhan, ... arXiv preprint arXiv:1705.06950, 2017 | 157 | 2017 |
| Learning and querying fast generative models for reinforcement learning L Buesing, T Weber, S Racaniere, SM Eslami, D Rezende, DP Reichert, ... arXiv preprint arXiv:1802.03006, 2018 | 115 | 2018 |
| The DeepMind JAX Ecosystem, 2020 I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ... URL http://github. com/deepmind 18, 2010 | 111 | 2010 |
| On the role of planning in model-based deep reinforcement learning JB Hamrick, AL Friesen, F Behbahani, A Guez, F Viola, S Witherspoon, ... arXiv preprint arXiv:2011.04021, 2020 | 90 | 2020 |
| Muesli: Combining improvements in policy optimization M Hessel, I Danihelka, F Viola, A Guez, S Schmitt, L Sifre, T Weber, ... International conference on machine learning, 4214-4226, 2021 | 83 | 2021 |
| The DeepMind JAX Ecosystem I Babuschkin, K Baumli, A Bell, S Bhupatiraju, J Bruce, P Buchlovsky, ... URL http://github. com/deepmind 24, 25, 2020 | 74 | 2020 |
| Counterfactual credit assignment in model-free reinforcement learning T Mesnard, T Weber, F Viola, S Thakoor, A Saade, A Harutyunyan, ... arXiv preprint arXiv:2011.09464, 2020 | 72 | 2020 |
| Distortion-free image mosaicing for tunnel inspection based on robust cylindrical surface estimation through structure from motion K Chaiyasarn, TK Kim, F Viola, R Cipolla, K Soga Journal of Computing in Civil Engineering 30 (3), 04015045, 2016 | 65 | 2016 |
| The kinetics human action video dataset A Zisserman, J Carreira, K Simonyan, W Kay, B Zhang, C Hillier, ... arXiv preprint arXiv 1705, 2017 | 55 | 2017 |
| Roto++ accelerating professional rotoscoping using shape manifolds W Li, F Viola, J Starck, GJ Brostow, NDF Campbell ACM Transactions on Graphics (TOG) 35 (4), 1-15, 2016 | 52 | 2016 |
| Optax: composable gradient transformation and optimisation M Hessel, D Budden, F Viola, M Rosca, E Sezener, T Hennigan JAX, http://github. com/deepmind/optax (last access: 4 July 2023), version 0.0 1, 2020 | 50 | 2020 |
