| 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 | 7657 | 2016 |
| Universal transformers M Dehghani, S Gouws, O Vinyals, J Uszkoreit, Ł Kaiser International Conference on Learning Representations (ICLR), 2019 | 802 | 2019 |
| Tensor2tensor for neural machine translation A Vaswani, S Bengio, E Brevdo, F Chollet, AN Gomez, S Gouws, L Jones, ... arXiv preprint arXiv:1803.07416, 2018 | 581 | 2018 |
| Bilbowa: Fast bilingual distributed representations without word alignments S Gouws, Y Bengio, G Corrado International Conference on Machine Learning (ICML), 2015 | 428 | 2015 |
| Google¢s neural machine translation system: Bridging the gap between human and machine translation. arXiv 2016 Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144 2, 2019 | 271 | 2019 |
| Generating high-quality and informative conversation responses with sequence-to-sequence models Y Shao, S Gouws, D Britz, A Goldie, B Strope, R Kurzweil Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 216 | 2017 |
| Simple task-specific bilingual word embeddings S Gouws, A Søgaard Proceedings of the 2015 Conference of the North American Chapter of the …, 2015 | 163 | 2015 |
| XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings A Royer, K Bousmalis, S Gouws, F Bertsch, I Moressi, F Cole, K Murphy arXiv preprint arXiv:1711.05139, 2017 | 143 | 2017 |
| Contextual bearing on linguistic variation in social media S Gouws, D Metzler, C Cai, E Hovy Proceedings of the workshop on language in social media (LSM 2011), 20-29, 2011 | 139 | 2011 |
| Google¢s neural machine translation system: Bridging the gap between human and machine translation. CoRR abs/1609.08144 (2016) Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... arXiv preprint arXiv:1609.08144, 2016 | 96 | 2016 |
| Fidelity-weighted learning M Dehghani, A Mehrjou, S Gouws, J Kamps, B Schölkopf arXiv preprint arXiv:1711.02799, 2017 | 73 | 2017 |
| Unsupervised mining of lexical variants from noisy text S Gouws, D Hovy, D Metzler Proceedings of the First workshop on Unsupervised Learning in NLP, 82-90, 2011 | 70 | 2011 |
| Generating long and diverse responses with neural conversation models L Shao, S Gouws, D Britz, A Goldie, B Strope, R Kurzweil arXiv preprint arXiv:1701.03185, 2017 | 69 | 2017 |
| Google¢s neural machine translation system: Bridging the gap between human and machine translation. CoRR abs/1609.08144 Y Wu, M Schuster, Z Chen, QV Le, M Norouzi, W Macherey, M Krikun, ... | 67 | 2016 |
| Measuring conceptual similarity by spreading activation over Wikipedia¢s hyperlink structure S Gouws, GJ Van Rooyen, HA Engelbrecht Proceedings of the 2nd Workshop on The People¢s Web Meets NLP …, 2010 | 42 | 2010 |
| Learning structural correspondences across different linguistic domains with synchronous neural language models S Gouws, GJ Van Rooyen, MIH Medialab, Y Bengio Proc. of the xLite Workshop on Cross-Lingual Technologies, NIPS, 2012 | 8 | 2012 |
| Deep unsupervised feature learning for natural language processing S Gouws Proceedings of the NAACL HLT 2012 Student Research Workshop, 48-53, 2012 | 7 | 2012 |
| Training neural word embeddings for transfer learning and translation S Gouws Stellenbosch: Stellenbosch University, 2016 | 2 | 2016 |
| Evaluation and development of conceptual document similarity metrics with content-based recommender applications S Gouws Stellenbosch: University of Stellenbosch, 2010 | 2 | 2010 |
| Learning from samples of variable quality M Dehghani, A Mehrjou, S Gouws, J Kamps, B Schölkopf | 1 | 2019 |
Łukasz KaiserOpenAI & CNRSVerified email at openai.com
