6 citations · 6 across the 3 of their papers we have counts for
4 papers
A Monotone Single-Index Modal Regression Powered by Deep Neural Networks for Non-Gaussian Periodontal Data
Qingyang Liu, Shijie Wang, Ray Bai +1
Pocket depth (PD) is a widely used biomarker for diagnosing risk of periodontal disease (PrD). However, PD typically exhibits skewness and heavy-tailedness, and its relationship wi…
Neural-g: A Deep Learning Framework for Mixing Density Estimation
Shijie Wang, Saptarshi Chakraborty, Qian Qin +1
Mixing (or prior) density estimation is an important problem in machine learning and statistics, especially in empirical Bayes -modeling where accurately estimating the prior is…
Fast Bootstrapping Nonparametric Maximum Likelihood for Latent Mixture Models
Shijie Wang, Minsuk Shin, Ray Bai
Estimating the mixing density of a latent mixture model is an important task in signal processing. Nonparametric maximum likelihood estimation is one popular approach to this probl…
Bayesian Modal Regression based on Mixture Distributions
Qingyang Liu, Xianzheng Huang, Rai Bai
Compared to mean regression and quantile regression, the literature on modal regression is very sparse. A unifying framework for Bayesian modal regression is proposed, based on a f…