3 papers
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
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…
stat.AP2024
Robust Distributed Learning of Functional Data From Simulators through Data Sketching
R. Jacob Andros, Rajarshi Guhaniyogi, Devin Francom +1
In environmental studies, realistic simulations are essential for understanding complex systems. Statistical emulation with Gaussian processes (GPs) in functional data models have…