research
∙
01/09/2023
Generative Quantile Regression with Variability Penalty
Quantile regression and conditional density estimation can reveal struct...
share
research
∙
10/02/2020
Neural Bootstrapper
Bootstrapping has been a primary tool for uncertainty quantification, an...
research
∙
06/24/2020
Bayesian Shrinkage for Functional Network Models with Intractable Normalizing Constants
Longitudinal network models are widely used to study the time-varying re...
research
∙
06/01/2020
Scalable Uncertainty Quantification via GenerativeBootstrap Sampler
It has been believed that the virtue of using statistical procedures is ...
research
∙
05/28/2019
Generative Parameter Sampler For Scalable Uncertainty Quantification
Uncertainty quantification has been a core of the statistical machine le...
research
∙
10/11/2018
Stochastic Approximation Hamiltonian Monte Carlo
Recently, the Hamilton Monte Carlo (HMC) has become widespread as one of...
research
∙
09/29/2018