| Generating sentences from a continuous space SR Bowman, L Vilnis, O Vinyals, AM Dai, R Jozefowicz, S Bengio Proceedings of the 20th SIGNLL Conference on Computational Natural Language …, 2016 | 1340 | 2016 |
| Semi-supervised sequence learning AM Dai, QV Le Advances in neural information processing systems 28, 3079-3087, 2015 | 839 | 2015 |
| Scalable and accurate deep learning with electronic health records A Rajkomar, E Oren, K Chen, AM Dai, N Hajaj, M Hardt, PJ Liu, X Liu, ... NPJ Digital Medicine 1 (1), 18, 2018 | 739 | 2018 |
| HyperNetworks D Ha, A Dai, QV Le Proceedings of the International Conference on Learning Representations, 2017 | 508 | 2017 |
| Adversarial Training Methods for Semi-Supervised Text Classification T Miyato, AM Dai, I Goodfellow Proceedings of the International Conference on Learning Representations, 2017 | 370 | 2017 |
| Document embedding with paragraph vectors AM Dai, C Olah, QV Le NIPS 2014 Deep learning workshop, 2015 | 338 | 2015 |
| Natural questions: a benchmark for question answering research T Kwiatkowski, J Palomaki, O Redfield, M Collins, A Parikh, C Alberti, ... Transactions of the Association for Computational Linguistics 7, 453-466, 2019 | 305 | 2019 |
| MaskGAN: Better text generation via filling in the_ W Fedus, I Goodfellow, AM Dai arXiv preprint arXiv:1801.07736, 2018 | 263 | 2018 |
| Many paths to equilibrium: GANs do not need to decrease a divergence at every step W Fedus, M Rosca, B Lakshminarayanan, AM Dai, S Mohamed, ... arXiv preprint arXiv:1710.08446, 2017 | 126 | 2017 |
| Music transformer: Generating music with long-term structure CZA Huang, A Vaswani, J Uszkoreit, I Simon, C Hawthorne, N Shazeer, ... International Conference on Learning Representations, 2018 | 94 | 2018 |
| Who said what: Modeling individual labelers improves classification M Guan, V Gulshan, A Dai, G Hinton Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 81 | 2018 |
| Learning longer-term dependencies in rnns with auxiliary losses TH Trinh, AM Dai, MT Luong, QV Le arXiv preprint arXiv:1803.00144, 2018 | 78 | 2018 |
| Music transformer CZA Huang, A Vaswani, J Uszkoreit, N Shazeer, I Simon, C Hawthorne, ... arXiv preprint arXiv:1809.04281, 2018 | 54 | 2018 |
| Embedding text in hyperbolic spaces B Dhingra, CJ Shallue, M Norouzi, AM Dai, GE Dahl arXiv preprint arXiv:1806.04313, 2018 | 53 | 2018 |
| Language-independent compound splitting with morphological operations K Macherey, AM Dai, D Talbot, AC Popat, F Och | 53 | 2011 |
| Wearable sensors for Parkinson’s disease: which data are worth collecting for training symptom detection models L Lonini, A Dai, N Shawen, T Simuni, C Poon, L Shimanovich, ... NPJ digital medicine 1 (1), 1-8, 2018 | 45 | 2018 |
| The supervised hierarchical Dirichlet process AM Dai, AJ Storkey IEEE transactions on pattern analysis and machine intelligence 37 (2), 243-255, 2014 | 39 | 2014 |
| Gmail smart compose: Real-time assisted writing MX Chen, BN Lee, G Bansal, Y Cao, S Zhang, J Lu, J Tsay, Y Wang, ... Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 36 | 2019 |
| Compound splitting AM Dai, K Macherey, FJ Och, AC Popat, DR Talbot US Patent 9,075,792, 2015 | 30 | 2015 |
| An improved relative self-attention mechanism for transformer with application to music generation CZA Huang, A Vaswani, J Uszkoreit, N Shazeer, C Hawthorne, AM Dai, ... arXiv preprint arXiv:1809.04281 2, 2018 | 29 | 2018 |
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
