Jordon, James

18 publications

AISTATS 2023 To Impute or Not to Impute? Missing Data in Treatment Effect Estimation Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela Schaar

NeurIPSW 2022 TAPAS: A Toolbox for Adversarial Privacy Auditing of Synthetic Data Florimond Houssiau, James Jordon, Samuel N Cohen, Owen Daniel, Andrew Elliott, James Geddes, Callum Mole, Camila Rangel-Smith, Lukasz Szpruch

ICML 2021 Learning Queueing Policies for Organ Transplantation Allocation Using Interpretable Counterfactual Survival Analysis Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela Schaar

AISTATS 2020 Contextual Constrained Learning for Dose-Finding Clinical Trials Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela Schaar

ICLR 2020 Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar

NeurIPS 2020 Estimating the Effects of Continuous-Valued Interventions Using Generative Adversarial Networks Ioana Bica, James Jordon, Mihaela van der Schaar

ICLR 2020 Individualised Dose-Response Estimation Using Generative Adversarial Nets Ioana Bica, James Jordon, Mihaela van der Schaar

NeurIPS 2020 OrganITE: Optimal Transplant Donor Organ Offering Using an Individual Treatment Effect Jeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar

NeurIPS 2020 VIME: Extending the Success of Self- and Semi-Supervised Learning to Tabular Domain Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar

MLHC 2019 ASAC: Active Sensing Using Actor-Critic Models Jinsung Yoon, James Jordon, Mihaela Schaar

NeurIPS 2019 Differentially Private Bagging: Improved Utility and Cheaper Privacy than Subsample-and-Aggregate James Jordon, Jinsung Yoon, Mihaela van der Schaar

ICLR 2019 INVASE: Instance-Wise Variable Selection Using Neural Networks Jinsung Yoon, James Jordon, Mihaela van der Schaar

ICLR 2019 KnockoffGAN: Generating Knockoffs for Feature Selection Using Generative Adversarial Networks James Jordon, Jinsung Yoon, Mihaela van der Schaar

ICLR 2019 PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees James Jordon, Jinsung Yoon, Mihaela van der Schaar

AAAI 2018 Deep-Treat: Learning Optimal Personalized Treatments from Observational Data Using Neural Networks Onur Atan, James Jordon, Mihaela van der Schaar

ICML 2018 GAIN: Missing Data Imputation Using Generative Adversarial Nets Jinsung Yoon, James Jordon, Mihaela Schaar

ICLR 2018 GANITE: Estimation of Individualized Treatment Effects Using Generative Adversarial Nets Jinsung Yoon, James Jordon, Mihaela van der Schaar

ICML 2018 RadialGAN: Leveraging Multiple Datasets to Improve Target-Specific Predictive Models Using Generative Adversarial Networks Jinsung Yoon, James Jordon, Mihaela Schaar