1 citations · 1 across the 5 of their papers we have counts for
5 papers
A Comparison of Zero-Inflated Models for Modern Biomedical Data
Max Beveridge, Zach Goldstein, Hee Cheol Chung
Many data sets cannot be accurately described by standard probability distributions due to the excess number of zero values present. For example, zero-inflation is prevalent in mic…
Bayesian segmented Gaussian copula factor model for single-cell sequencing data
Junsouk Choi, Hee Cheol Chung, Irina Gaynanova +1
Single-cell sequencing technologies have significantly advanced molecular and cellular biology, offering unprecedented insights into cellular heterogeneity by allowing for the meas…
Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process Mixtures
Dongwook Kim, Juyeon Park, Hee Cheol Chung +1
Probabilistic mixture models are recognized as effective tools for unsupervised outlier detection owing to their interpretability and global characteristics. Among these, Dirichlet…
Sparse semiparametric discriminant analysis for high-dimensional zero-inflated data
Hee Cheol Chung, Yang Ni, Irina Gaynanova
Sequencing-based technologies provide an abundance of high-dimensional biological datasets with skewed and zero-inflated measurements. Classification of such data with linear discr…
Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks
Hee Cheol Chung, Irina Gaynanova, Yang Ni
Microorganisms play a critical role in host health. The advancement of high-throughput sequencing technology provides opportunities for a deeper understanding of microbial interact…