A Fully Bayesian Inference with Gibbs Sampling for Finite and Infinite Discrete Exponential Mixture Models-Reference-Cited by-同舟云学术

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A Fully Bayesian Inference with Gibbs Sampling for Finite and Infinite Discrete Exponential Mixture Models

Published:2022-03-15 Issue:1 Volume:36 Page:
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Su Xuanbo¹,Zamzami Nuha²,Bouguila Nizar¹^ORCID

Affiliation:

1. Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada

2. Department of Computer Science and Artificial Intelligence, University of Jeddah, College of Computer Science and Engineering, Jeddah, Saudi Arabia

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2043526

Reference48 articles.

1. Model Selection and Estimation of a Finite Shifted-Scaled Dirichlet Mixture Model

2. Birth-Death MCMC Approach for Multivariate Beta Mixture Models in Medical Applications

3. Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems

4. Multi-classifier System for Sentiment Analysis and Opinion Mining

5. Clustering of Count Data Using Generalized Dirichlet Multinomial Distributions

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A CVAE-within-Gibbs sampler for Bayesian linear inverse problems with hyperparameters;Computational and Applied Mathematics;2023-03-31

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