ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2005.06173
  4. Cited By
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"

5 / 5 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
10
1
0
12 Sep 2021
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
145
562
0
19 Mar 2017
Random Forest Missing Data Algorithms
Random Forest Missing Data Algorithms
Fei Tang
H. Ishwaran
48
515
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
741
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
247
9,042
0
06 Jun 2015
1