Forecasting urban household water demand with statistical and machine learning methods using large space-time data: A Comparative study. - Isaac Duerr; Hunter R. Merrill; Chuan Wang; Ray Bai; Mackenzie Boyer; Michael D. Dukes; Nikolay Bliznyuk (Environ. Model. Softw., 2018)

High-dimensional multivariate posterior consistency under global-local shrinkage priors. - Ray Bai; Malay Ghosh (J. Multivar. Anal., 2018)

Neighborhood deprivation increases the risk of Post-induction cesarean delivery. - Jessica R. Meeker; Heather Burris; Ray Bai; Lisa Levine; Mary Regina Boland (J. Am. Medical Informatics Assoc., 2022)

Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance. - Ray Bai; Mary Regina Boland; Yong Chen 016 (J. Mach. Learn. Res., 2023)

Neural-g: A Deep Learning Framework for Mixing Density Estimation. - Shijie Wang; Saptarshi Chakraborty; Qian Qin; Ray Bai (CoRR, 2024)

Bayesian modal regression based on mixture distributions. - Qingyang Liu; Xianzheng Huang; Ray Bai (Comput. Stat. Data Anal., 2024)

Generative Quantile Regression with Variability Penalty. - Shijie Wang; Minsuk Shin; Ray Bai (J. Comput. Graph. Stat., 2024)

Fast Bootstrapping Nonparametric Maximum Likelihood for Latent Mixture Models. - Shijie Wang; Minsuk Shin; Ray Bai (IEEE Signal Process. Lett., 2024)

Sparse high-dimensional linear mixed modeling with a partitioned empirical Bayes ECM algorithm. - Anja Zgodic; Ray Bai; Jiajia Zhang; Peter Olejua; Alexander C. McLain (Stat. Comput., 2025)