| TensorFlow: Large-scale machine learning on heterogeneous systems, 2015 M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... Software available from tensorflow. org, 0 | 60306* | |
| 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 | 36480 | 2021 |
| Sequence to sequence learning with neural networks I Sutskever, O Vinyals, QV Le Advances in neural information processing systems 27, 2014 | 29692 | 2014 |
| Distilling the knowledge in a neural network G Hinton, O Vinyals, J Dean arXiv preprint arXiv:1503.02531, 2015 | 25750 | 2015 |
| Representation learning with contrastive predictive coding A Oord, Y Li, O Vinyals arXiv preprint arXiv:1807.03748, 2018 | 11953 | 2018 |
| Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, D Wierstra Advances in neural information processing systems 29, 2016 | 11552* | 2016 |
| Neural message passing for quantum chemistry J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl International conference on machine learning, 1263-1272, 2017 | 10579 | 2017 |
| Google's neural machine translation system: Bridging the gap between human and machine translation Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144, 2016 | 9687 | 2016 |
| Show and tell: A neural image caption generator O Vinyals, A Toshev, S Bengio, D Erhan Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 8429 | 2015 |
| 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 | 6368 | 2016 |
| Decaf: A deep convolutional activation feature for generic visual recognition J Donahue, Y Jia, O Vinyals, J Hoffman, N Zhang, E Tzeng, T Darrell International conference on machine learning, 647-655, 2014 | 6326 | 2014 |
| Neural discrete representation learning A Van Den Oord, O Vinyals Advances in neural information processing systems 30, 2017 | 6220 | 2017 |
| Understanding deep learning requires rethinking generalization C Zhang, S Bengio, M Hardt, B Recht, O Vinyals arXiv preprint arXiv:1611.03530, 2016 | 5599 | 2016 |
| 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 | 5436 | 2019 |
| Flamingo: a visual language model for few-shot learning JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ... Advances in neural information processing systems 35, 23716-23736, 2022 | 4864 | 2022 |
| Wavenet: A generative model for raw audio A Oord, S Dieleman, H Zen, K Simonyan, O Vinyals, A Graves, ... arXiv preprint arXiv:1609.03499, 2016 | 4830* | 2016 |
| 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 | 4443 | 2023 |
| Relational inductive biases, deep learning, and graph networks PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 4254 | 2018 |
| Pointer networks O Vinyals, M Fortunato, N Jaitly Advances in neural information processing systems 28, 2015 | 4166 | 2015 |
| Recurrent neural network regularization W Zaremba, I Sutskever, O Vinyals arXiv preprint arXiv:1409.2329, 2014 | 4151 | 2014 |
Jeff DeanGoogle Chief Scientist, Google Research and Google DeepMindVerified email at google.com