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 | 1367 | 2018 |
Time-series generative adversarial networks J Yoon, D Jarrett, M Van der Schaar Advances in neural information processing systems 32, 2019 | 1222 | 2019 |
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 | 920 | 2021 |
PATE-GAN: Generating synthetic data with differential privacy guarantees J Jordon, J Yoon, M van der Schaar International Conference on Learning Representations, 2018 | 800 | 2018 |
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 | 659 | 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 | 481 | 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 | 359* | 2018 |
Vime: Extending the success of self-and semi-supervised learning to tabular domain J Yoon, Y Zhang, J Jordon, M Van der Schaar Advances in Neural Information Processing Systems 33, 11033-11043, 2020 | 278 | 2020 |
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 | 272 | 2019 |
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 | 267 | 2018 |
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 | 262 | 2020 |
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 | 242 | 2020 |
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022 | 232 | 2022 |
Data valuation using reinforcement learning J Yoon, S Arik, T Pfister International Conference on Machine Learning, 10842-10851, 2020 | 223 | 2020 |
INVASE: Instance-wise variable selection using neural networks J Yoon, J Jordon, M van der Schaar International Conference on Learning Representations, 2018 | 197 | 2018 |
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 | 109* | 2017 |
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 | 101 | 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 | 94 | 2016 |
KnockoffGAN: Generating knockoffs for feature selection using generative adversarial networks J Jordon, J Yoon, M van der Schaar International Conference on Learning Representations, 2018 | 92 | 2018 |
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Medrxiv, 2021.02. 03.21250974, 2021 | 91 | 2021 |