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Multiple Imputation for Biomedical Data using Monte Carlo Dropout
  Autoencoders

Multiple Imputation for Biomedical Data using Monte Carlo Dropout Autoencoders

13 May 2020
Kristian Miok
Dong Nguyen Doan
Marko Robnik-Šikonja
D. Zaharie
    SyDa
ArXivPDFHTML

Papers citing "Multiple Imputation for Biomedical Data using Monte Carlo Dropout Autoencoders"

7 / 7 papers shown
Title
Estimating a new panel MSK dataset for comparative analyses of national
  absorptive capacity systems, economic growth, and development in low and
  middle income economies
Estimating a new panel MSK dataset for comparative analyses of national absorptive capacity systems, economic growth, and development in low and middle income economies
M. S. Khan
20
1
0
12 Sep 2021
Bayesian Methods for Semi-supervised Text Annotation
Bayesian Methods for Semi-supervised Text Annotation
Kristian Miok
Gregor Pirš
Marko Robnik-Šikonja
BDL
34
5
0
28 Oct 2020
Encouraging an Appropriate Representation Simplifies Training of Neural
  Networks
Encouraging an Appropriate Representation Simplifies Training of Neural Networks
Krisztián Búza
21
0
0
17 Nov 2019
Generating Multi-label Discrete Patient Records using Generative
  Adversarial Networks
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
E. Choi
Siddharth Biswal
B. Malin
J. Duke
Walter F. Stewart
Jimeng Sun
SyDa
GAN
156
569
0
19 Mar 2017
Random Forest Missing Data Algorithms
Random Forest Missing Data Algorithms
Fei Tang
H. Ishwaran
55
524
0
19 Jan 2017
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
197
745
0
06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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