| Character-aware neural language models Y Kim, Y Jernite, D Sontag, A Rush Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 1473 | 2016 |
| Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning S Horng, DA Sontag, Y Halpern, Y Jernite, NI Shapiro, LA Nathanson PloS one 12 (4), e0174708, 2017 | 123 | 2017 |
| Discourse-based objectives for fast unsupervised sentence representation learning Y Jernite, SR Bowman, D Sontag arXiv preprint arXiv:1705.00557, 2017 | 56 | 2017 |
| Transformers: State-of-the-art natural language processing T Wolf, J Chaumond, L Debut, V Sanh, C Delangue, A Moi, P Cistac, ... Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 47 | 2020 |
| Variable computation in recurrent neural networks Y Jernite, E Grave, A Joulin, T Mikolov arXiv preprint arXiv:1611.06188, 2016 | 43 | 2016 |
| Eli5: Long form question answering A Fan, Y Jernite, E Perez, D Grangier, J Weston, M Auli arXiv preprint arXiv:1907.09190, 2019 | 35 | 2019 |
| The random subgraph model for the analysis of an ecclesiastical network in Merovingian Gaul Y Jernite, P Latouche, C Bouveyron, P Rivera, L Jegou, S Lamassé The Annals of Applied Statistics 8 (1), 377-405, 2014 | 31 | 2014 |
| Simultaneous learning of trees and representations for extreme classification and density estimation Y Jernite, A Choromanska, D Sontag International Conference on Machine Learning, 1665-1674, 2017 | 24 | 2017 |
| Discovering hidden variables in noisy-or networks using quartet tests Y Jernite, Y Halpern, D Sontag Advances in Neural Information Processing Systems 26, 2355-2363, 2013 | 24 | 2013 |
| A fast variational approach for learning Markov random field language models Y Jernite, A Rush, D Sontag International Conference on Machine Learning, 2209-2217, 2015 | 23 | 2015 |
| Predicting chief complaints at triage time in the emergency department Y Jernite, Y Halpern, S Horng, D Sontag NIPS 2013 Workshop on Machine Learning for Clinical Data Analysis and Healthcare, 2013 | 19 | 2013 |
| Grounded recurrent neural networks A Vani, Y Jernite, D Sontag arXiv preprint arXiv:1705.08557, 2017 | 14 | 2017 |
| KILT: a benchmark for knowledge intensive language tasks F Petroni, A Piktus, A Fan, P Lewis, M Yazdani, N De Cao, J Thorne, ... arXiv preprint arXiv:2009.02252, 2020 | 9 | 2020 |
| Contextual autocomplete: A novel user interface using machine learning to improve ontology usage and structured data capture for presenting problems in the emergency department NR Greenbaum, Y Jernite, Y Halpern, S Calder, LA Nathanson, D Sontag, ... BioRxiv, 127092, 2017 | 7 | 2017 |
| Craftassist: A framework for dialogue-enabled interactive agents J Gray, K Srinet, Y Jernite, H Yu, Z Chen, D Guo, S Goyal, CL Zitnick, ... arXiv preprint arXiv:1907.08584, 2019 | 6 | 2019 |
| Improving conditioning in context-aware sequence to sequence models X Wang, J Weston, M Auli, Y Jernite arXiv preprint arXiv:1911.09728, 2019 | 5 | 2019 |
| Why Build an Assistant in Minecraft? A Szlam, J Gray, K Srinet, Y Jernite, A Joulin, G Synnaeve, D Kiela, H Yu, ... arXiv preprint arXiv:1907.09273, 2019 | 4 | 2019 |
| Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces NR Greenbaum, Y Jernite, Y Halpern, S Calder, LA Nathanson, ... International journal of medical informatics 132, 103981, 2019 | 3 | 2019 |
| CraftAssist instruction parsing: semantic parsing for a minecraft assistant Y Jernite, K Srinet, J Gray, A Szlam arXiv preprint arXiv:1905.01978, 2019 | 2 | 2019 |
| CraftAssist Instruction Parsing: Semantic Parsing for a Voxel-World Assistant K Srinet, Y Jernite, J Gray Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | | 2020 |
David SontagAssociate Professor, Massachusetts Institute of TechnologyBestätigte E-Mail-Adresse bei csail.mit.edu
