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06/26/2022
Scalable and optimal Bayesian inference for sparse covariance matrices via screened beta-mixture prior
In this paper, we propose a scalable Bayesian method for sparse covarian...
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06/01/2022
Asymptotic Properties for Bayesian Neural Network in Besov Space
Neural networks have shown great predictive power when dealing with vari...
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01/31/2022
Estimation of World Seroprevalence of SARS-CoV-2 antibodies
In this paper, we estimate the seroprevalence against COVID-19 by countr...
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11/04/2021
Covariance Structure Estimation with Laplace Approximation
Gaussian covariance graph model is a popular model in revealing underlyi...
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10/10/2021
Ordinary Differential Equation Models and their Computation Methods
In this article, I introduce the differential equation model and review ...
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08/26/2021
Multivariate Lévy Adaptive B-Spline Regression
We develop a fully Bayesian nonparametric regression model based on a Lé...
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08/21/2021
Post-Processed Posteriors for Sparse Covariances and Its Application to Global Minimum Variance Portfolio
We consider Bayesian inference of sparse covariance matrices and propose...
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08/10/2021
Identifiability of Covariance Kernels in the Gaussian Process Regression Model
Gaussian process regression (GPR) model is a popular nonparametric regre...
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07/30/2021
Bayesian Nonparametric Classification for Incomplete Data With a High Missing Rate: an Application to Semiconductor Manufacturing Data
During the semiconductor manufacturing process, predicting the yield of ...
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04/07/2021
Laplace-aided variational inference for differential equation models
Ordinary differential equation (ODE) model whose regression curves are a...
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03/11/2021
Estimation of Conditional Mean Operator under the Bandable Covariance Structure
We consider high-dimensional multivariate linear regression models, wher...
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01/28/2021
Lévy Adaptive B-spline Regression via Overcomplete Systems
The estimation of functions with varying degrees of smoothness is a chal...
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01/28/2021
Seroprevalence of SARS-CoV-2 antibodies in South Korea
In 2020, Korea Disease Control and Prevention Agency reported three roun...
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01/12/2021
The Beta-Mixture Shrinkage Prior for Sparse Covariances with Posterior Minimax Rates
Statistical inference for sparse covariance matrices is crucial to revea...
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12/08/2020
Robust Sparse Bayesian Infinite Factor Models
Most of previous works and applications of Bayesian factor model have as...
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11/25/2020
Post-Processed Posteriors for Banded Covariances
We consider Bayesian inference of banded covariance matrices and propose...
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11/19/2020
Variational Bayes method for ODE parameter estimation with application to time-varying SIR model for Covid-19 epidemic
Ordinary differential equation (ODE) is a mathematical model for dynamic...
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11/15/2018
Minimax Posterior Convergence Rates and Model Selection Consistency in High-dimensional DAG Models based on Sparse Cholesky Factors
In this paper, we study the high-dimensional sparse directed acyclic gra...
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04/05/2011