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We propose a novel method for imputing missing data by adapting the well-known Generative Adversarial Nets (GAN) framework.
Multiple-imputation inferences with uncongenial sources of input
Meng, X.-L · 1994
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Applications of multiple imputation in medical studies: from aids to nhanes
Barnard, J. and Meng, X.-L · 1999
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Multivariate imputation by chained equations: Mice v1. 0 user’s manual
Buuren, S. v. and Oudshoorn, C · 2000
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Multiple imputation for nonresponse in surveys , volume 81
Rubin, D. B · 2004
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Extracting and composing robust features with denoising autoencoders
Vincent, P., Larochelle, H., Bengio, Y., and Manzagol, P.-A · 2008
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Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls
Sterne, J. A., White, I. R., Carlin, J. B., Spratt, M., Royston, P., Kenward, M. G., Wood, A. M., and Carpenter, J. R · 2009
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Active sensing
Yu, S., Krishnapuram, B., Rosales, R., and Rao, R. B · 2009
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Pattern classification with missing data: a review
García-Laencina, P. J., Sancho-Gómez, J.-L., and Figueiras-Vidal, A. R · 2010
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MNIST handwritten digit database
LeCun, Y. and Cortes, C · 2010
Cited alongside, same era.
The use and reporting of multiple imputation in medical research–a review
Mackinnon, A · 2010
Cited alongside, same era.
mice: Multivariate imputation by chained equations in r
Buuren, S. and Groothuis-Oudshoorn, K · 2011
Cited alongside, same era.
Missforest—non-parametric missing value imputation for mixed-type data
Stekhoven, D. J. and Bühlmann, P · 2011
Cited alongside, same era.
The effects of the irregular sample and missing data in time series analysis
Kreindler, D. M. and Lumsden, C. J · 2012
Cited alongside, same era.
Combining multiple imputation and meta-analysis with individual participant data
Burgess, S., White, I. R., Resche-Rigon, M., and Wood, A. M · 2013
Cited alongside, same era.
Hybrid prediction model with missing value imputation for medical data
Purwar, A. and Singh, S. K · 2015
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Generative Adversarial Denoising Autoencoder for Face Completion , 2016
Allen, A. and Li, W · 2016
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Multiple imputation for general missing data patterns in the presence of high-dimensional data
Deng, Y., Chang, C., Ido, M. S., and Long, Q · 2016
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Recommendations as treatments: debiasing learning and evolution
Schnabel, T., Swaminatan, A., Singh, A., Chandak, N., and Joachims, T · 2016
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Temporal regularized matrix factorization for high-dimensional time series prediction
Yu, H.-F., Rao, H., and Dhillon, I. S · 2016
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UCI machine learning repository, 2013
Lichman, M · 2013
Cited alongside, same era.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
Cited alongside, same era.
Spectral regularization algorithms for learning large incomplete matrices
Mazumder, R., Hastie, T., and Tibshirani, R
Cited in the paper.
Spectral regularization algorithms for learning large incomplete matrices
Mazumder, R., Hastie, T., and Tibshirani, R
Cited in the paper.
GANITE: Estimation of individualized treatment effects using generative adversarial nets
Yoon, J., Jordon, J., and van der Schaar, M
Cited in the paper.
Personalized survival predictions via trees of predictors: An application to cardiac transplantation
Yoon, J., Zame, W. R., Banerjee, A., Cadeiras, M., Alaa, A. M., and van der Schaar, M
Cited in the paper.
Gondara, L. and Wang, K · 2017
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Discovery and clinical decision support for personalized healthcare
Yoon, J., Davtyan, C., and van der Schaar, M · 2017
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Personalized risk scoring for critical care prognosis using mixtures of gaussian processes
Alaa, A. M., Yoon, J., Hu, S., and van der Schaar, M · 2018
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