| Gain: Missing data imputation using generative adversarial nets J Yoon, J Jordon, M Van Der Schaar International Conference on Machine Learning 80, 5689--5698, 2018 | 528 | 2018 |
| PATE-GAN: Generating synthetic data with differential privacy guarantees J Jordon, J Yoon, M van der Schaar International Conference on Learning Representations, 2018 | 282 | 2018 |
| Time-series generative adversarial networks J Yoon, D Jarrett, M Van der Schaar Advances in neural information processing systems 32, 2019 | 264 | 2019 |
| Deephit: A deep learning approach to survival analysis with competing risks C Lee, W Zame, J Yoon, M Van Der Schaar Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 255 | 2018 |
| GANITE: Estimation of individualized treatment effects using generative adversarial nets J Yoon, J Jordon, M van der Schaar International Conference on Learning Representations, 2018 | 214 | 2018 |
| Sex differences in outcomes after STEMI: effect modification by treatment strategy and age E Cenko, J Yoon, S Kedev, G Stankovic, Z Vasiljevic, G Krljanac, ... JAMA Internal Medicine 178 (5), 632-639, 2018 | 147 | 2018 |
| Estimating missing data in temporal data streams using multi-directional recurrent neural networks J Yoon, WR Zame, M van der Schaar IEEE Transactions on Biomedical Engineering 66 (5), 1477-1490, 2018 | 122* | 2018 |
| Cutpaste: Self-supervised learning for anomaly detection and localization CL Li, K Sohn, J Yoon, T Pfister Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 113 | 2021 |
| INVASE: Instance-wise variable selection using neural networks J Yoon, J Jordon, M van der Schaar International Conference on Learning Representations, 2018 | 99 | 2018 |
| Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis with Competing Risks based on Longitudinal Data C Lee, J Yoon, M Van Der Schaar IEEE Transactions on Biomedical Engineering 67 (1), 122--133, 2019 | 92 | 2019 |
| Personalized risk scoring for critical care prognosis using mixtures of gaussian processes AM Alaa, J Yoon, S Hu, M Van der Schaar IEEE Transactions on Biomedical Engineering 65 (1), 207-218, 2017 | 73* | 2017 |
| Learning and evaluating representations for deep one-class classification K Sohn, CL Li, J Yoon, M Jin, T Pfister arXiv preprint arXiv:2011.02578, 2020 | 72 | 2020 |
| Discovery and clinical decision support for personalized healthcare J Yoon, C Davtyan, M van der Schaar IEEE Journal of Biomedical and Health Informatics 21 (4), 1133-1145, 2016 | 66 | 2016 |
| Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, AJC Rivadeneira, ... Medrxiv, 2021 | 64 | 2021 |
| Data valuation using reinforcement learning J Yoon, S Arik, T Pfister International Conference on Machine Learning, 10842-10851, 2020 | 58 | 2020 |
| Anonymization through data synthesis using generative adversarial networks (ads-gan) J Yoon, LN Drumright, M Van Der Schaar IEEE journal of biomedical and health informatics 24 (8), 2378-2388, 2020 | 56 | 2020 |
| Interpretable sequence learning for COVID-19 forecasting S Arik, CL Li, J Yoon, R Sinha, A Epshteyn, L Le, V Menon, S Singh, ... Advances in Neural Information Processing Systems 33, 18807-18818, 2020 | 53 | 2020 |
| Sex-related differences in heart failure after ST-segment elevation myocardial infarction E Cenko, M van der Schaar, J Yoon, O Manfrini, Z Vasiljevic, M Vavlukis, ... Journal of the American College of Cardiology 74 (19), 2379-2389, 2019 | 53 | 2019 |
| KnockoffGAN: Generating knockoffs for feature selection using generative adversarial networks J Jordon, J Yoon, M van der Schaar International Conference on Learning Representations, 2018 | 52 | 2018 |
| Personalized survival predictions via Trees of Predictors: An application to cardiac transplantation J Yoon, WR Zame, A Banerjee, M Cadeiras, AM Alaa, M van der Schaar PloS ONE 13 (3), 2018 | 48 | 2018 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing InstituteΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα ee.ucla.edu
