| Recurrent neural networks for multivariate time series with missing values Z Che, S Purushotham, K Cho, D Sontag, Y Liu Scientific reports 8 (1), 6085, 2018 | 2383 | 2018 |
| Character-aware neural language models Y Kim, Y Jernite, D Sontag, AM Rush Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 2210 | 2016 |
| Estimating individual treatment effect: generalization bounds and algorithms U Shalit, F Johansson, D Sontag Proceedings of the International Conference on Machine Learning (ICML), 2017 | 1205 | 2017 |
| Learning Representations for Counterfactual Inference FD Johansson, U Shalit, D Sontag 33rd International Conference on Machine Learning (ICML), 2016 | 883 | 2016 |
| Causal Effect Inference with Deep Latent-Variable Models C Louizos, U Shalit, J Mooij, D Sontag, R Zemel, M Welling Neural Information Processing Systems (NIPS) 31, 2017 | 871 | 2017 |
| BLOG: Probabilistic models with unknown objects B Milch, B Marthi, S Russell, D Sontag, DL Ong, A Kolobov Introduction to statistical relational learning, 373, 2007 | 619 | 2007 |
| A practical algorithm for topic modeling with provable guarantees S Arora, R Ge, Y Halpern, D Mimno, A Moitra, D Sontag, Y Wu, M Zhu Proceedings of the International Conference on Machine Learning (ICML), 280--288, 2013 | 566 | 2013 |
| Structured inference networks for nonlinear state space models RG Krishnan, U Shalit, D Sontag Thirty-First AAAI Conference on Artificial Intelligence, 2017 | 550 | 2017 |
| Why is my classifier discriminatory? I Chen, FD Johansson, D Sontag NeurIPS, 2018 | 531 | 2018 |
| Learning a health knowledge graph from electronic medical records M Rotmensch, Y Halpern, A Tlimat, S Horng, D Sontag Scientific reports 7 (1), 5994, 2017 | 494 | 2017 |
| Guidelines for reinforcement learning in healthcare O Gottesman, F Johansson, M Komorowski, A Faisal, D Sontag, ... Nature medicine 25 (1), 16-18, 2019 | 476 | 2019 |
| Deep kalman filters RG Krishnan, U Shalit, D Sontag arXiv preprint arXiv:1511.05121, 2015 | 450 | 2015 |
| Learning Low-Dimensional Representations of Medical Concepts Y Choi, CYI Chiu, D Sontag Proceedings of the AMIA Summit on Clinical Research Informatics (CRI), 2016 | 390 | 2016 |
| Tightening LP relaxations for MAP using message passing D Sontag, T Meltzer, A Globerson, T Jaakkola, Y Weiss Uncertainty in Artificial Intelligence (UAI) 24, 2008 | 369* | 2008 |
| Large language models are few-shot clinical information extractors M Agrawal, S Hegselmann, H Lang, Y Kim, D Sontag Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 347 | 2022 |
| Unsupervised learning of disease progression models X Wang, D Sontag, F Wang Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 325 | 2014 |
| 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 | 306 | 2017 |
| Learning Bayesian network structure using LP relaxations T Jaakkola, D Sontag, A Globerson, M Meila Proceedings of the thirteenth international conference on artificial …, 2010 | 297 | 2010 |
| Semi-amortized variational autoencoders Y Kim, S Wiseman, AC Miller, D Sontag, AM Rush ICML, 2018 | 290 | 2018 |
| Population-level prediction of type 2 diabetes from claims data and analysis of risk factors N Razavian, S Blecker, AM Schmidt, A Smith-McLallen, S Nigam, ... Big Data 3 (4), 277-287, 2015 | 274 | 2015 |
Fredrik D. JohanssonAssociate Professor, Chalmers University of Technology在 chalmers.se 的电子邮件经过验证
