Nonparametric variational learning of multivariate beta mixture models in medical applications-Reference-Cited by-同舟云学术

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Nonparametric variational learning of multivariate beta mixture models in medical applications

Published:2020-10-20 Issue:1 Volume:31 Page:128-140
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Technol

Author:

Manouchehri Narges¹^ORCID,Bouguila Nizar¹^ORCID,Fan Wentao²

Affiliation:

1. Concordia Institute for Information Systems Engineering Concordia University, Montreal Quebec Canada

2. Department of Computer Science and Technology Huaqiao University Xiamen China

Funder

National Natural Science Foundation of China

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22506

Reference52 articles.

1. Analyzing Microarray Gene Expression Data

2. Pattern Recognition and Machine Learning

3. Unsupervised Learning of a Finite Mixture Model Based on the Dirichlet Distribution and Its Application

4. A gamma mixture model better accounts for among site rate heterogeneity;Mayrose I;Bioinformatics,2005

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3. Maximum Likelihood-Based Estimation of Finite Multivariate Libby-Novick Beta Mixture Models in Medical Applications;2023 IEEE International Conference on Industrial Technology (ICIT);2023-04-04

4. Finite Multivariate McDonald's Beta Mixture Model Learning Approach in Medical Applications;Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing;2023-03-27

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