| Sequence to sequence learning with neural networks I Sutskever, O Vinyals, QV Le arXiv preprint arXiv:1409.3215, 2014 | 17729 | 2014 |
| Distributed representations of sentences and documents Q Le, T Mikolov International conference on machine learning, 1188-1196, 2014 | 8928 | 2014 |
| 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 | 5402 | 2016 |
| Efficientnet: Rethinking model scaling for convolutional neural networks M Tan, Q Le International Conference on Machine Learning, 6105-6114, 2019 | 5223 | 2019 |
| Xlnet: Generalized autoregressive pretraining for language understanding Z Yang, Z Dai, Y Yang, J Carbonell, R Salakhutdinov, QV Le arXiv preprint arXiv:1906.08237, 2019 | 4108 | 2019 |
| Learning transferable architectures for scalable image recognition B Zoph, V Vasudevan, J Shlens, QV Le Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 3829 | 2018 |
| Large scale Distributed Deep Networks AYN J. Dean, G.S. Corrado, R. Monga, K. Chen, M. Devin Advances In Neural Information Processing Systems 25 (7), 2012 | 3699* | 2012 |
| Neural architecture search with reinforcement learning B Zoph, QV Le arXiv preprint arXiv:1611.01578, 2016 | 3678 | 2016 |
| Building high-level features using large scale unsupervised learning QV Le, MA Ranzato, R Monga, M Devin, K Chen, GS Corrado, J Dean, ... International Conference on Machine Learning, 2012 | 2688 | 2012 |
| 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 | 2077* | 2016 |
| Searching for activation functions P Ramachandran, B Zoph, QV Le arXiv preprint arXiv:1710.05941, 2017 | 1906* | 2017 |
| A neural conversational model O Vinyals, Q Le arXiv preprint arXiv:1506.05869, 2015 | 1865 | 2015 |
| Regularized evolution for image classifier architecture search E Real, A Aggarwal, Y Huang, QV Le Proceedings of the aaai conference on artificial intelligence 33 (01), 4780-4789, 2019 | 1805 | 2019 |
| Efficient neural architecture search via parameters sharing H Pham, M Guan, B Zoph, Q Le, J Dean International Conference on Machine Learning, 4095-4104, 2018 | 1798 | 2018 |
| Autoaugment: Learning augmentation policies from data ED Cubuk, B Zoph, D Mane, V Vasudevan, QV Le arXiv preprint arXiv:1805.09501, 2018 | 1772* | 2018 |
| Transformer-xl: Attentive language models beyond a fixed-length context Z Dai, Z Yang, Y Yang, J Carbonell, QV Le, R Salakhutdinov arXiv preprint arXiv:1901.02860, 2019 | 1693 | 2019 |
| Searching for mobilenetv3 A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 1676 | 2019 |
| Mnasnet: Platform-aware neural architecture search for mobile M Tan, B Chen, R Pang, V Vasudevan, M Sandler, A Howard, QV Le Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 1614 | 2019 |
| Google’s multilingual neural machine translation system: Enabling zero-shot translation M Johnson, M Schuster, QV Le, M Krikun, Y Wu, Z Chen, N Thorat, ... Transactions of the Association for Computational Linguistics 5, 339-351, 2017 | 1491 | 2017 |
| Exploiting similarities among languages for machine translation T Mikolov, QV Le, I Sutskever arXiv preprint arXiv:1309.4168, 2013 | 1491 | 2013 |
Barret ZophStaff Research Scientist, Google BrainEmail verificata su google.com
