James Jordon - RankMe

31 papers A* 9A 2Journal 14Unranked 6

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Reinforcement Learning applied to Insurance Portfolio Pursuit. CoRR Edward James Young, Alistair Rogers, Elliott Tong, James Jordon
2023	A	`conf`	To Impute or not to Impute? Missing Data in Treatment Effect Estimation. AISTATS Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar
2022	J	`jnl`	Synthetic Data - what, why and how? CoRR James Jordon, Lukasz Szpruch, Florimond Houssiau, Mirko Bottarelli, Giovanni Cherubin, Carsten Maple, Samuel N. Cohen, Adrian Weller
2022	J	`jnl`	TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data. CoRR Florimond Houssiau, James Jordon, Samuel N. Cohen, Owen Daniel, Andrew Elliott, James Geddes, Callum D. Mole, Camila Rangel Smith, Lukasz Szpruch
2022	J	`jnl`	To Impute or not to Impute? - Missing Data in Treatment Effect Estimation. CoRR Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar
2021	A*	`conf`	Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis. ICML Jeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar
2020	A	`conf`	Contextual Constrained Learning for Dose-Finding Clinical Trials. AISTATS Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela van der Schaar
2020	J	`jnl`	Contextual Constrained Learning for Dose-Finding Clinical Trials. CoRR Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela van der Schaar
2020	J	`jnl`	Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations. CoRR Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar
2020	A*	`conf`	Estimating counterfactual treatment outcomes over time through adversarially balanced representations. ICLR Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar
2020	A*	`conf`	Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. NeurIPS Ioana Bica, James Jordon, Mihaela van der Schaar
2020	J	`jnl`	Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. CoRR Ioana Bica, James Jordon, Mihaela van der Schaar
2020	J	`jnl`	Hide-and-Seek Privacy Challenge. CoRR James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar
2020	—	`conf`	Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification. NeurIPS (Competition and Demos) James Jordon, Daniel Jarrett, Evgeny Saveliev, Jinsung Yoon, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar
2020	A*	`conf`	OrganITE: Optimal transplant donor organ offering using an individual treatment effect. NeurIPS Jeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar
2020	J	`jnl`	Synthetic Data: Opening the data floodgates to enable faster, more directed development of machine learning methods. CoRR James Jordon, Alan Wilson, Mihaela van der Schaar
2020	A*	`conf`	VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain. NeurIPS Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar
2019	—	`conf`	ASAC: Active Sensing using Actor-Critic models. MLHC Jinsung Yoon, James Jordon, Mihaela van der Schaar
2019	J	`jnl`	ASAC: Active Sensing using Actor-Critic models. CoRR Jinsung Yoon, James Jordon, Mihaela van der Schaar
2019	A*	`conf`	Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate. NeurIPS James Jordon, Jinsung Yoon, Mihaela van der Schaar
2019	—	`conf`	INVASE: Instance-wise Variable Selection using Neural Networks. ICLR (Poster) Jinsung Yoon, James Jordon, Mihaela van der Schaar
2019	—	`conf`	KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks. ICLR James Jordon, Jinsung Yoon, Mihaela van der Schaar
2019	J	`jnl`	Lifelong Bayesian Optimization. CoRR Yao Zhang, James Jordon, Ahmed M. Alaa, Mihaela van der Schaar
2019	—	`conf`	PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees. ICLR (Poster) James Jordon, Jinsung Yoon, Mihaela van der Schaar
2018	A*	`conf`	Deep-Treat: Learning Optimal Personalized Treatments From Observational Data Using Neural Networks. AAAI Onur Atan, James Jordon, Mihaela van der Schaar
2018	A*	`conf`	GAIN: Missing Data Imputation using Generative Adversarial Nets. ICML Jinsung Yoon, James Jordon, Mihaela van der Schaar
2018	J	`jnl`	GAIN: Missing Data Imputation using Generative Adversarial Nets. CoRR Jinsung Yoon, James Jordon, Mihaela van der Schaar
2018	—	`conf`	GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets. ICLR (Poster) Jinsung Yoon, James Jordon, Mihaela van der Schaar
2018	J	`jnl`	Measuring the quality of Synthetic data for use in competitions. CoRR James Jordon, Jinsung Yoon, Mihaela van der Schaar
2018	A*	`conf`	RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. ICML Jinsung Yoon, James Jordon, Mihaela van der Schaar
2018	J	`jnl`	RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. CoRR Jinsung Yoon, James Jordon, Mihaela van der Schaar