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01/26/2022
A Kernel-Based Approach for Modelling Gaussian Processes with Functional Information
Gaussian processes are among the most useful tools in modeling continuou...
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10/11/2021
Bayesian Regularization for Functional Graphical Models
Graphical models, used to express conditional dependence between random ...
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07/22/2019
Coupling material and mechanical design processes via computer model calibration
Computer model calibration typically operates by choosing parameter valu...
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11/02/2018
Efficient Marginalization-based MCMC Methods for Hierarchical Bayesian Inverse Problems
Hierarchical models in Bayesian inverse problems are characterized by an...
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03/29/2018
A Large Scale Spatio-temporal Binomial Regression Model for Estimating Seroprevalence Trends
This paper develops a large-scale Bayesian spatio-temporal binomial regr...
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10/27/2017