| 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 | 39803* | |
| Sequence to sequence learning with neural networks I Sutskever, O Vinyals, QV Le Advances in neural information processing systems 27, 2014 | 19713 | 2014 |
| Distilling the knowledge in a neural network G Hinton, O Vinyals, J Dean arXiv preprint arXiv:1503.02531 2 (7), 2015 | 10739 | 2015 |
| 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 | 6063 | 2016 |
| 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 | 5970* | 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 | 5822 | 2015 |
| 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 | 5163 | 2014 |
| Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, D Wierstra Advances in neural information processing systems 29, 2016 | 4698 | 2016 |
| 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 | 4550 | 2021 |
| Understanding deep learning (still) requires rethinking generalization C Zhang, S Bengio, M Hardt, B Recht, O Vinyals Communications of the ACM 64 (3), 107-115, 2021 | 4322 | 2021 |
| Neural message passing for quantum chemistry J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl International conference on machine learning, 1263-1272, 2017 | 4030 | 2017 |
| Representation learning with contrastive predictive coding A Oord, Y Li, O Vinyals arXiv preprint arXiv:1807.03748, 2018 | 3181 | 2018 |
| Recurrent neural network regularization W Zaremba, I Sutskever, O Vinyals arXiv preprint arXiv:1409.2329, 2014 | 2713 | 2014 |
| Beyond short snippets: Deep networks for video classification J Yue-Hei Ng, M Hausknecht, S Vijayanarasimhan, O Vinyals, R Monga, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 2451 | 2015 |
| Pointer networks O Vinyals, M Fortunato, N Jaitly Advances in neural information processing systems 28, 2015 | 2448 | 2015 |
| Listen, attend and spell: A neural network for large vocabulary conversational speech recognition W Chan, N Jaitly, Q Le, O Vinyals 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 2355* | 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 | 2134 | 2019 |
| 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 | 2081 | 2018 |
| Generating sentences from a continuous space SR Bowman, L Vilnis, O Vinyals, AM Dai, R Jozefowicz, S Bengio arXiv preprint arXiv:1511.06349, 2015 | 2064 | 2015 |
| A neural conversational model O Vinyals, Q Le arXiv preprint arXiv:1506.05869, 2015 | 1951 | 2015 |
