James Jordon
James Jordon
Research Assistant, The Alan Turing Institute
Verified email at wolfson.ox.ac.uk
Title
Cited by
Cited by
Year
Gain: Missing data imputation using generative adversarial nets
J Yoon, J Jordon, M Schaar
International Conference on Machine Learning, 5689-5698, 2018
3032018
PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees
J Jordon, J Yoon, M van der Schaar
1502018
GANITE: Estimation of individualized treatment effects using generative adversarial nets
J Yoon, J Jordon, M Van Der Schaar
International Conference on Learning Representations, 2018
1352018
INVASE: Instance-wise Variable Selection using Neural Networks
J Yoon, J Jordon, M van der Schaar
572018
Estimating counterfactual treatment outcomes over time through adversarially balanced representations
I Bica, AM Alaa, J Jordon, M van der Schaar
arXiv preprint arXiv:2002.04083, 2020
362020
Deep-Treat: Learning Optimal Personalized Treatments From Observational Data Using Neural Networks.
O Atan, J Jordon, M van der Schaar
AAAI, 2018
352018
Lifelong Bayesian Optimization
Y Zhang, J Jordon, AM Alaa, M van der Schaar
arXiv preprint arXiv:1905.12280, 2019
26*2019
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
J Yoon, J Jordon, M van der Schaar
arXiv preprint arXiv:1802.06403, 2018
202018
Measuring the quality of Synthetic data for use in competitions
J Jordon, J Yoon, M van der Schaar
arXiv preprint arXiv:1806.11345, 2018
192018
KnockoffGAN: Generating Knockoffs for Feature Selection using Generative Adversarial Networks
J Jordon, J Yoon, M van der Schaar
162018
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks
I Bica, J Jordon, M van der Schaar
arXiv preprint arXiv:2002.12326, 2020
102020
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate
J Jordon, J Yoon, M van der Schaar
Advances in Neural Information Processing Systems, 4325-4334, 2019
92019
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, 2020
82020
Hide-and-Seek Privacy Challenge
J Jordon, D Jarrett, J Yoon, T Barnes, P Elbers, P Thoral, A Ercole, ...
arXiv preprint arXiv:2007.12087, 2020
62020
Contextual Constrained Learning for Dose-Finding Clinical Trials
HS Lee, C Shen, J Jordon, M van der Schaar
arXiv preprint arXiv:2001.02463, 2020
62020
ASAC: Active Sensing using Actor-Critic models
J Yoon, J Jordon, M van der Schaar
arXiv preprint arXiv:1906.06796, 2019
42019
OrganITE: Optimal transplant donor organ offering using an individual treatment effect
J Berrevoets, J Jordon, I Bica, M van der Schaar
Advances in Neural Information Processing Systems 33, 2020
22020
Synthetic Data: Opening the data floodgates to enable faster, more directed development of machine learning methods
J Jordon, A Wilson, M van der Schaar
arXiv preprint arXiv:2012.04580, 2020
12020
Supplementary Materials GAIN: Missing Data Imputation using Generative Adversarial Nets
J Yoon, J Jordon, M van der Schaar
1*
Hide-and-Seek Privacy Challenge: Synthetic Data Generation vs. Patient Re-identification
J Jordon, D Jarrett, E Saveliev, J Yoon, P Elbers, P Thoral, A Ercole, ...
NeurIPS 2020 Competition and Demonstration Track, 206-215, 2021
2021
The system can't perform the operation now. Try again later.
Articles 1–20