collaborators

5 papers

stat.CO2026

All Emulators are Wrong, Many are Useful, and Some are More Useful Than Others: A Reproducible Comparison of Computer Model Surrogates

Kellin N. Rumsey, Graham C. Gibson, Devin Francom +1

Accurate and efficient surrogate modeling is essential for modern computational science, and there are a staggering number of emulation methods to choose from. With new methods bei…

stat.ME2026

Supervised Learning of Functional Outcomes with Predictors at Different Scales: A Functional Gaussian Process Approach

R. Jacob Andros, Rajarshi Guhaniyogi, Devin Francom +1

The analysis of complex computer simulations, often involving functional data, presents unique statistical challenges. Conventional regression methods, such as function-on-function…

stat.ME2025

Bayesian Adaptive Polynomial Chaos Expansions

Kellin N. Rumsey, Devin Francom, Graham C. Gibson +2

Polynomial chaos expansions (PCE) are widely used for uncertainty quantification (UQ) tasks, particularly in the applied mathematics community. However, PCE has received comparativ…

stat.ME2025

A Review and Comparison of Different Sensitivity Analysis Techniques in Practice

Devin Francom, Abigael Nachtsheim

There exist many methods for sensitivity analysis readily available to the practitioner. While each seeks to help the modeler answer the same general question -- How do sources of…

stat.ME2025

Interpretable Deep Neural Network for Modeling Functional Surrogates

Yeseul Jeon, Rajarshi Guhaniyogi, Aaron Scheffler +2

Developing surrogates for computer models has become increasingly important for addressing complex problems in science and engineering. This article introduces an artificial intell…