| 2023 | AISTATS | To Impute or not to Impute? Missing Data in Treatment Effect Estimation. | Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar |
| 2021 | ICML | Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis. | Jeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar |
| 2020 | AISTATS | Contextual Constrained Learning for Dose-Finding Clinical Trials. | Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela van der Schaar |
| 2020 | ICLR | Estimating counterfactual treatment outcomes over time through adversarially balanced representations. | Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar |
| 2019 | ICLR | KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks. | James Jordon, Jinsung Yoon, Mihaela van der Schaar |
| 2019 | ICLR | PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees. | James Jordon, Jinsung Yoon, Mihaela van der Schaar |
| 2019 | ICLR | INVASE: Instance-wise Variable Selection using Neural Networks. | Jinsung Yoon, James Jordon, Mihaela van der Schaar |
| 2018 | AAAI | Deep-Treat: Learning Optimal Personalized Treatments From Observational Data Using Neural Networks. | Onur Atan, James Jordon, Mihaela van der Schaar |
| 2018 | ICLR | GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets. | Jinsung Yoon, James Jordon, Mihaela van der Schaar |
| 2018 | ICML | GAIN: Missing Data Imputation using Generative Adversarial Nets. | Jinsung Yoon, James Jordon, Mihaela van der Schaar |
| 2018 | ICML | RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. | Jinsung Yoon, James Jordon, Mihaela van der Schaar |