research
∙
06/02/2023
Bayesian Segmentation Modeling of Epidemic Growth
Tracking the spread of infectious disease during a pandemic has posed a ...
share
research
∙
05/26/2023
A Policy Gradient Method for Confounded POMDPs
In this paper, we propose a policy gradient method for confounded partia...
research
∙
10/23/2022
Functional Bayesian Networks for Discovering Causality from Multivariate Functional Data
Multivariate functional data arise in a wide range of applications. One ...
research
∙
10/20/2022
Bayesian Tensor-on-Tensor Regression with Efficient Computation
We propose a Bayesian tensor-on-tensor regression approach to predict a ...
research
∙
09/18/2022
Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes
We study the offline reinforcement learning (RL) in the face of unmeasur...
research
∙
07/21/2022
Bayesian Sparse Gaussian Mixture Model in High Dimensions
We establish the minimax risk for parameter estimation in sparse high-di...
research
∙
05/20/2021
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation
This paper presents a computational framework that generates ensemble pr...
research
∙
07/08/2020
Personalized Dynamic Treatment Regimes in Continuous Time: A Bayesian Joint Model for Optimizing Clinical Decisions with Timing
Accurate models of clinical actions and their impacts on disease progres...
research
∙
07/03/2020
BAGEL: A Bayesian Graphical Model for Inferring Drug Effect Longitudinally on Depression in People with HIV
Access and adherence to antiretroviral therapy (ART) has transformed the...
research
∙
04/11/2020
A Bayesian Nonparametric Approach for Inferring Drug Combination Effects on Mental Health in People with HIV
Although combination antiretroviral therapy (ART) is highly effective in...
research
∙
10/10/2019
Efficient Estimation for Random Dot Product Graphs via a One-step Procedure
We propose a one-step procedure to efficiently estimate the latent posit...
research
∙
04/26/2019
Optimal Bayesian Estimation for Random Dot Product Graphs
We propose a Bayesian approach, called the posterior spectral embedding,...
research
∙
03/20/2019
A Bayesian Nonparametric Approach for Evaluating the Effect of Treatment in Randomized Trials with Semi-Competing Risks
We develop a Bayesian nonparametric (BNP) approach to evaluate the effec...
research
∙
02/15/2019
BAREB: A Bayesian repulsive biclustering model for periodontal data
Preventing periodontal diseases (PD) and maintaining the structure and f...
research
∙
10/04/2018
ASIED: A Bayesian Adaptive Subgroup-Identification Enrichment Design
Developing targeted therapies based on patients' baseline characteristic...
research
∙
08/22/2018
Bayesian Estimation of Sparse Spiked Covariance Matrices in High Dimensions
We propose a Bayesian methodology for estimating spiked covariance matri...
research
∙
03/03/2018
Bayesian Projected Calibration of Computer Models
We develop a Bayesian approach called Bayesian projected calibration to ...
research
∙
12/15/2017
A Theoretical Framework for Bayesian Nonparametric Regression: Orthonormal Random Series and Rates of Contraction
We develop a unifying framework for Bayesian nonparametric regression to...
research
∙
11/30/2017
Nonseparable Gaussian Stochastic Process: A Unified View and Computational Strategy
Gaussian stochastic process (GaSP) has been widely used as a prior over ...
research
∙
10/22/2017
Adaptive Bayesian nonparametric regression using kernel mixture of polynomials with application to partial linear model
We propose a kernel mixture of polynomials prior for Bayesian nonparamet...
research
∙
08/18/2016
