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ORCIDJames Jordon
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2020 – today
- 2024
[i14]Edward James Young, Alistair Rogers, Elliott Tong, James Jordon:
Reinforcement Learning applied to Insurance Portfolio Pursuit. CoRR abs/2408.00713 (2024)- 2023
- [c17]Jeroen Berrevoets
, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar:
To Impute or not to Impute? Missing Data in Treatment Effect Estimation. AISTATS 2023: 3568-3590 - 2022
- [i13]Jeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar:
To Impute or not to Impute? - Missing Data in Treatment Effect Estimation. CoRR abs/2202.02096 (2022) - [i12]James Jordon, Lukasz Szpruch, Florimond Houssiau, Mirko Bottarelli, Giovanni Cherubin, Carsten Maple, Samuel N. Cohen, Adrian Weller:
Synthetic Data - what, why and how? CoRR abs/2205.03257 (2022) - [i11]Florimond Houssiau, James Jordon, Samuel N. Cohen, Owen Daniel, Andrew Elliott, James Geddes, Callum D. Mole, Camila Rangel Smith, Lukasz Szpruch:
TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data. CoRR abs/2211.06550 (2022) - 2021
- [c16]Jeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar:
Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis. ICML 2021: 792-802 - 2020
- [c15]Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela van der Schaar:
Contextual Constrained Learning for Dose-Finding Clinical Trials. AISTATS 2020: 2645-2654 - [c14]Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar:
Estimating counterfactual treatment outcomes over time through adversarially balanced representations. ICLR 2020 - [c13]Jeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar:
OrganITE: Optimal transplant donor organ offering using an individual treatment effect. NeurIPS 2020 - [c12]Ioana Bica, James Jordon, Mihaela van der Schaar:
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. NeurIPS 2020 - [c11]James Jordon, Daniel Jarrett, Evgeny Saveliev, Jinsung Yoon, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar:
Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification. NeurIPS (Competition and Demos) 2020: 206-215 - [c10]Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar:
VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain. NeurIPS 2020 - [i10]Hyun-Suk Lee, Cong Shen, James Jordon, Mihaela van der Schaar:
Contextual Constrained Learning for Dose-Finding Clinical Trials. CoRR abs/2001.02463 (2020) - [i9]Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar:
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations. CoRR abs/2002.04083 (2020) - [i8]Ioana Bica, James Jordon, Mihaela van der Schaar:
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. CoRR abs/2002.12326 (2020) - [i7]James Jordon, Daniel Jarrett, Jinsung Yoon, Tavian Barnes, Paul W. G. Elbers, Patrick Thoral, Ari Ercole, Cheng Zhang, Danielle Belgrave, Mihaela van der Schaar:
Hide-and-Seek Privacy Challenge. CoRR abs/2007.12087 (2020) - [i6]James Jordon, Alan Wilson, Mihaela van der Schaar:
Synthetic Data: Opening the data floodgates to enable faster, more directed development of machine learning methods. CoRR abs/2012.04580 (2020)
2010 – 2019
- 2019
- [c9]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks. ICLR 2019 - [c8]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees. ICLR (Poster) 2019 - [c7]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
INVASE: Instance-wise Variable Selection using Neural Networks. ICLR (Poster) 2019 - [c6]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
ASAC: Active Sensing using Actor-Critic models. MLHC 2019: 451-473 - [c5]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate. NeurIPS 2019: 4325-4334 - [i5]Yao Zhang, James Jordon, Ahmed M. Alaa, Mihaela van der Schaar:
Lifelong Bayesian Optimization. CoRR abs/1905.12280 (2019) - [i4]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
ASAC: Active Sensing using Actor-Critic models. CoRR abs/1906.06796 (2019) - 2018
- [c4]Onur Atan, James Jordon, Mihaela van der Schaar:
Deep-Treat: Learning Optimal Personalized Treatments From Observational Data Using Neural Networks. AAAI 2018: 2071-2078 - [c3]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets. ICLR (Poster) 2018 - [c2]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
GAIN: Missing Data Imputation using Generative Adversarial Nets. ICML 2018: 5675-5684 - [c1]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. ICML 2018: 5685-5693 - [i3]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks. CoRR abs/1802.06403 (2018) - [i2]Jinsung Yoon, James Jordon, Mihaela van der Schaar:
GAIN: Missing Data Imputation using Generative Adversarial Nets. CoRR abs/1806.02920 (2018) - [i1]James Jordon, Jinsung Yoon, Mihaela van der Schaar:
Measuring the quality of Synthetic data for use in competitions. CoRR abs/1806.11345 (2018)
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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