| Human-level control through deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ... nature 518 (7540), 529-533, 2015 | 34657 | 2015 |
| Highly accurate protein structure prediction with AlphaFold J Jumper, R Evans, A Pritzel, T Green, M Figurnov, O Ronneberger, ... nature 596 (7873), 583-589, 2021 | 33551 | 2021 |
| Mastering the game of Go with deep neural networks and tree search D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ... nature 529 (7587), 484-489, 2016 | 21299 | 2016 |
| Playing atari with deep reinforcement learning V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ... arXiv preprint arXiv:1312.5602, 2013 | 17115 | 2013 |
| Asynchronous methods for deep reinforcement learning V Mnih, AP Badia, M Mirza, A Graves, T Lillicrap, T Harley, D Silver, ... International conference on machine learning, 1928-1937, 2016 | 12691 | 2016 |
| Natural language processing (almost) from scratch R Collobert, J Weston, L Bottou, M Karlen, K Kavukcuoglu, P Kuksa | 10624 | 2011 |
| Spatial transformer networks M Jaderberg, K Simonyan, A Zisserman Advances in neural information processing systems 28, 2015 | 9829 | 2015 |
| Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, D Wierstra Advances in neural information processing systems 29, 2016 | 9108 | 2016 |
| Bootstrap your own latent-a new approach to self-supervised learning JB Grill, F Strub, F Altché, C Tallec, P Richemond, E Buchatskaya, ... Advances in neural information processing systems 33, 21271-21284, 2020 | 7658 | 2020 |
| Wavenet: A generative model for raw audio A Van Den Oord, S Dieleman, H Zen, K Simonyan, O Vinyals, A Graves, ... arXiv preprint arXiv:1609.03499 12, 2016 | 6162 | 2016 |
| Neural discrete representation learning A Van Den Oord, O Vinyals Advances in neural information processing systems 30, 2017 | 5631 | 2017 |
| Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... nature 575 (7782), 350-354, 2019 | 5177 | 2019 |
| Recurrent models of visual attention V Mnih, N Heess, A Graves, K Kavukcuoglu Advances in neural information processing systems 27, 2014 | 5064 | 2014 |
| Weight uncertainty in neural network C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra International conference on machine learning, 1613-1622, 2015 | 4559 | 2015 |
| Improved protein structure prediction using potentials from deep learning AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre, T Green, C Qin, ... Nature 577 (7792), 706-710, 2020 | 3617 | 2020 |
| 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 | 3600 | 2023 |
| Progressive neural networks AA Rusu, NC Rabinowitz, G Desjardins, H Soyer, J Kirkpatrick, ... arXiv preprint arXiv:1606.04671, 2016 | 3321 | 2016 |
| What is the best multi-stage architecture for object recognition? K Jarrett, K Kavukcuoglu, MA Ranzato, Y LeCun 2009 IEEE 12th international conference on computer vision, 2146-2153, 2009 | 3226 | 2009 |
| Convolutional networks and applications in vision Y LeCun, K Kavukcuoglu, C Farabet Proceedings of 2010 IEEE international symposium on circuits and systems
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| Pixel recurrent neural networks A Van Den Oord, N Kalchbrenner, K Kavukcuoglu International conference on machine learning, 1747-1756, 2016 | 3059 | 2016 |
David SilverDeepMind, UCLPatvirtintas el. paštas google.com
