| Time-series Generative Adversarial Networks J Yoon*, D Jarrett*, M van der Schaar Neural Information Processing Systems (NeurIPS), 2019 | 1005 | 2019 |
| How Artificial Intelligence and Machine Learning can Help Healthcare Systems Respond to COVID-19 M van der Schaar, A Alaa, A Floto, AE Gimson, S Scholtes, A Wood, ... Machine Learning (Mach. Learn.), 2021 | 168 | 2021 |
| Applications and Limitations of Machine Learning in Radiation Oncology D Jarrett, E Stride, K Vallis, MJ Gooding The British Journal of Radiology (BJR), 2019 | 166 | 2019 |
| Dynamic Prediction in Clinical Survival Analysis using Temporal Convolutional Networks D Jarrett, J Yoon, M van der Schaar IEEE Journal of Biomedical and Health Informatics (JBHI), 2019 | 74 | 2019 |
| Strictly Batch Imitation Learning by Energy-based Distribution Matching D Jarrett*, I Bica*, M van der Schaar Neural Information Processing Systems (NeurIPS), 2020 | 52 | 2020 |
| HyperImpute: Generalized Iterative Imputation with Automatic Model Selection D Jarrett*, B Cebere*, T Liu, A Curth, M van der Schaar International Conference on Machine Learning (ICML), 2022 | 44 | 2022 |
| Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification J Jordon, D Jarrett, E Saveliev, J Yoon, P Elbers, P Thoral, A Ercole, ... Neural Information Processing Systems (NeurIPS), 2020 | 41 | 2020 |
| Invariant Causal Imitation Learning for Generalizable Policies I Bica*, D Jarrett*, M van der Schaar Neural Information Processing Systems (NeurIPS), 2021 | 37 | 2021 |
| Clairvoyance: A Pipeline Toolkit for Medical Time Series D Jarrett*, J Yoon*, I Bica, Z Qian, A Ercole, M van der Schaar International Conference on Learning Representations (ICLR), 2021 | 36 | 2021 |
| Learning "What-If" Explanations for Sequential Decision-Making I Bica, D Jarrett, A Hüyük, M van der Schaar International Conference on Learning Representations (ICLR), 2021 | 35 | 2021 |
| Inverse Decision Modeling: Learning Interpretable Representations of Behavior D Jarrett*, A Hüyük*, M van der Schaar International Conference on Machine Learning (ICML), 2021 | 30 | 2021 |
| Time-series Generation by Contrastive Imitation D Jarrett, I Bica, M van der Schaar Neural Information Processing Systems (NeurIPS), 2021 | 29 | 2021 |
| Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning A Hüyük*, D Jarrett*, C Tekin, M van der Schaar International Conference on Learning Representations (ICLR), 2021 | 25 | 2021 |
| Inverse Active Sensing: Modeling and Understanding Timely Decision-Making D Jarrett, M van der Schaar International Conference on Machine Learning (ICML), 2020 | 21 | 2020 |
| Medkit-Learn(ing) Environment: Medical Decision Modeling through Simulation AJ Chan, I Bica, A Hüyük, D Jarrett, M van der Schaar Neural Information Processing Systems (NeurIPS), 2021 | 16 | 2021 |
| Inverse Contextual Bandits: Learning How Behavior Evolves over Time A Hüyük*, D Jarrett*, M van der Schaar International Conference on Machine Learning (ICML), 2022 | 15 | 2022 |
| Target-Embedding Autoencoders for Supervised Representation Learning D Jarrett, M van der Schaar International Conference on Learning Representations (ICLR), 2020 | 15 | 2020 |
| Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments D Jarrett, C Tallec, F Altché, T Mesnard, R Munos, M Valko International Conference on Machine Learning (ICML), 2023 | 11 | 2023 |
| Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning Y Zhang, D Jarrett, M van der Schaar Artificial Intelligence and Statistics (AISTATS), 2020 | 11 | 2020 |
| Match-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks D Jarrett, J Yoon, M van der Schaar Machine Learning for Health Workshop (NeurIPS), 2018 | 10 | 2018 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing Institute在 ee.ucla.edu 的电子邮件经过验证
