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Dirichlet process mixture models with multiple modalities [PDF]
2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009 The Dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. The set of parameters over which it is defined is generally used for a single, parametric distribution.
John W. Paisley, Lawrence Carin
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Dirichlet process mixture models with shrinkage prior
Stat, 2021 We propose Dirichlet process mixture (DPM) models for prediction and cluster‐wise variable selection, based on two choices of shrinkage baseline prior distributions for the linear regression coefficients, namely, the Horseshoe prior and the Normal‐Gamma prior.
Dawei Ding, George Karabatsos
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BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures
Journal of Statistical Software, 2021 BNPmix is an R package for Bayesian nonparametric multivariate density estimation, clustering, and regression, using Pitman-Yor mixture models, a flexible and robust generalization of the popular class of Dirichlet process mixture models.
Riccardo Corradin +2 more
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Journal of Advanced Transportation, 2022 Interpretation of flexible cycling behavior has always been a tough task. It is meaningful to understand the overtaking behavior of cyclists for its threats to safety and its high frequency on shared roads.
Ailing Yin, Xiaohong Chen, Lishengsa Yue
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Classification of pulsars with Dirichlet process Gaussian mixture model [PDF]
Monthly Notices of the Royal Astronomical Society, 2020 ABSTRACT Young isolated neutron stars (INSs) most commonly manifest themselves as rotationally powered pulsars that involve conventional radio pulsars as well as gamma-ray pulsars and rotating radio transients. Some other young INS families manifest themselves as anomalous X-ray pulsars and soft gamma-ray repeaters that are commonly ...
K Yavuz Ekşi +3 more
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Machinery Early Fault Detection Based on Dirichlet Process Mixture Model
IEEE Access, 2019 The most commonly used single feature-based anomaly detection method for the complex machinery, such as large wind power equipment, steam turbine generator sets, and reciprocating compressors, exhibits a defect of low-alarm accuracy due to the non ...
Bo Ma +4 more
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Scientific Reports, 2021 Pancreatic Ductal Adenocarcinoma (PDAC) is the most lethal type of pancreatic cancer, late detection leading to its therapeutic failure. This study aims to determine the key regulatory genes and their impacts on the disease’s progression, helping the ...
Sk Md Mosaddek Hossain +4 more
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A New Single Image Super-Resolution Method Based on the Infinite Mixture Model
IEEE Access, 2017 As a powerful nonparametric Bayesian model, the infinite mixture model has been successfully used in machine learning and computer vision. The success of the infinite mixture model owes to the capability clustering and density estimation.
Peitao Cheng +3 more
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Dirichlet Process Parsimonious Mixtures for clustering
CoRR, 2015 The parsimonious Gaussian mixture models, which exploit an eigenvalue decomposition of the group covariance matrices of the Gaussian mixture, have shown their success in particular in cluster analysis. Their estimation is in general performed by maximum likelihood estimation and has also been considered from a parametric Bayesian prospective.
Faicel Chamroukhi +2 more
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Modeling and visualizing uncertainty in gene expression clusters using Dirichlet process mixtures [PDF]
, 2009 Although the use of clustering methods has rapidly become one of the standard computational approaches in the literature of microarray gene expression data, little attention has been paid to uncertainty in the results obtained. Dirichlet process mixture (
Rasmussen, Carl Edward +7 more
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