3 citations · 4 across the 5 of their papers we have counts for
6 papers
Conditional Dirichlet Processes and Functional Condition Models
Jaeyong Lee, Kwangmin Lee, Jaegui Lee +1
In this paper, we study the conditional Dirichlet process (cDP) when a functional of a random distribution is specified. Specifically, we apply the cDP to the functional condition…
Scalable and optimal Bayesian inference for sparse covariance matrices via screened beta-mixture prior
Kyoungjae Lee, Seongil Jo, Kyeongwon Lee +1
In this paper, we propose a scalable Bayesian method for sparse covariance matrix estimation by incorporating a continuous shrinkage prior with a screening procedure. In the first…
Seroprevalence of SARS-CoV-2 antibodies in South Korea
Kwangmin Lee, Seongil Jo, Jaeyong Lee
In , Korea Disease Control and Prevention Agency reported three rounds of surveys on seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies…
The Beta-Mixture Shrinkage Prior for Sparse Covariances with Posterior Minimax Rates
Kyoungjae Lee, Seongil Jo, Jaeyong Lee
Statistical inference for sparse covariance matrices is crucial to reveal dependence structure of large multivariate data sets, but lacks scalable and theoretically supported Bayes…
Robust Sparse Bayesian Infinite Factor Models
Jaejoon Lee, Jaeyong Lee
Most of previous works and applications of Bayesian factor model have assumed the normal likelihood regardless of its validity. We propose a Bayesian factor model for heavy-tailed…
Multilevel Monte Carlo in Approximate Bayesian Computation
Ajay Jasra, Seongil Jo, David Nott +2
In the following article we consider approximate Bayesian computation (ABC) inference. We introduce a method for numerically approximating ABC posteriors using the multilevel Monte…