| Distributed Representations of Words and Phrases and Their Compositionality T Mikolov arXiv preprint arXiv:1310.4546, 2013 | 44800 | 2013 |
| Efficient estimation of word representations in vector space T Mikolov arXiv preprint arXiv:1301.3781, 2013 | 43493 | 2013 |
| TensorFlow: Large-scale machine learning on heterogeneous systems M Abadi, A Agarwal, P Barham, E Brevdo, Z Chen, C Citro, GS Corrado, ... | 31270* | 2015 |
| Google’s neural machine translation system: Bridging the gap between human and machine translation Y Wu arXiv preprint arXiv:1609.08144, 2016 | 8874 | 2016 |
| Large Scale Distributed Deep Networks AYN Jeffrey Dean, Greg S. Corrado, Rajat Monga, Kai Advances in Neural Information Processing Systems, 1232-1240, 2012 | 4897* | 2012 |
| Wide & deep learning for recommender systems HT Cheng, L Koc, J Harmsen, T Shaked, T Chandra, H Aradhye, ... Proceedings of the 1st workshop on deep learning for recommender systems, 7-10, 2016 | 4100 | 2016 |
| Devise: A deep visual-semantic embedding model A Frome, GS Corrado, J Shlens, S Bengio, J Dean, MA Ranzato, ... Advances in neural information processing systems 26, 2013 | 3324 | 2013 |
| A guide to deep learning in healthcare A Esteva, A Robicquet, B Ramsundar, V Kuleshov, M DePristo, K Chou, ... Nature medicine 25 (1), 24-29, 2019 | 3191 | 2019 |
| Building high-level features using large scale unsupervised learning QV Le 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 3106 | 2013 |
| International evaluation of an AI system for breast cancer screening SM McKinney, M Sieniek, V Godbole, J Godwin, N Antropova, H Ashrafian, ... Nature 577 (7788), 89-94, 2020 | 2479 | 2020 |
| 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 | 2359 | 2017 |
| 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), 1-10, 2018 | 2269 | 2018 |
| End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography D Ardila, AP Kiraly, S Bharadwaj, B Choi, JJ Reicher, L Peng, D Tse, ... Nature medicine 25 (6), 954-961, 2019 | 1810 | 2019 |
| Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning R Poplin, AV Varadarajan, K Blumer, Y Liu, MV McConnell, GS Corrado, ... Nature biomedical engineering 2 (3), 158-164, 2018 | 1642 | 2018 |
| Key challenges for delivering clinical impact with artificial intelligence CJ Kelly, A Karthikesalingam, M Suleyman, G Corrado, D King BMC medicine 17, 1-9, 2019 | 1627 | 2019 |
| Large language models encode clinical knowledge K Singhal, S Azizi, T Tu, SS Mahdavi, J Wei, HW Chung, N Scales, ... Nature 620 (7972), 172-180, 2023 | 1569 | 2023 |
| Matching behavior and the representation of value in the parietal cortex LP Sugrue, GS Corrado, WT Newsome science 304 (5678), 1782-1787, 2004 | 1218 | 2004 |
| Stimulus onset quenches neural variability: a widespread cortical phenomenon MM Churchland, BM Yu, JP Cunningham, LP Sugrue, MR Cohen, ... Nature neuroscience 13 (3), 369-378, 2010 | 1179 | 2010 |
| Zero-shot learning by convex combination of semantic embeddings M Norouzi, T Mikolov, S Bengio, Y Singer, J Shlens, A Frome, GS Corrado, ... arXiv preprint arXiv:1312.5650, 2013 | 1098 | 2013 |
| Detecting cancer metastases on gigapixel pathology images Y Liu, K Gadepalli, M Norouzi, GE Dahl, T Kohlberger, A Boyko, ... arXiv preprint arXiv:1703.02442, 2017 | 773 | 2017 |
Tomas MikolovSenior Researcher, CIIRC CTU在 cvut.cz 的电子邮件经过验证