3 papers
stat.ME2024
Combining Climate Models using Bayesian Regression Trees and Random Paths
John C. Yannotty, Thomas J. Santner, Bo Li +1
General circulation models (GCMs) are essential tools for climate studies. Such climate models may have varying accuracy across the input domain, but no model is uniformly best. On…
nucl-th2023
Taweret: a Python package for Bayesian model mixing
Kevin Ingles, Dananjaya Liyanage, Alexandra C. Semposki +1
Uncertainty quantification using Bayesian methods is a growing area of research. Bayesian model mixing (BMM) is a recent development which combines the predictions from multiple mo…
stat.ME2023
Model Mixing Using Bayesian Additive Regression Trees
John C. Yannotty, Thomas J. Santner, Richard J. Furnstahl +1
In modern computer experiment applications, one often encounters the situation where various models of a physical system are considered, each implemented as a simulator on a comput…