185 citations · 228 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
Elastic Bayesian Model Calibration
Devin Francom, J. Derek Tucker, Gabriel Huerta +2
Functional data are ubiquitous in scientific modeling. For instance, quantities of interest are modeled as functions of time, space, energy, density, etc. Uncertainty quantificatio…
Elastic -means clustering of functional data for posterior exploration, with an application to inference on acute respiratory infection dynamics
Xiao Zang, Sebastian Kurtek, Oksana Chkrebtii +1
We propose a new method for clustering of functional data using a -means framework. We work within the elastic functional data analysis framework, which allows for decomposition…
Multimodal Bayesian Registration of Noisy Functions using Hamiltonian Monte Carlo
J. Derek Tucker, Lyndsay Shand, Kenny Chowdhary
Functional data registration is a necessary processing step for many applications. The observed data can be inherently noisy, often due to measurement error or natural process unce…
Regression Models Using Shapes of Functions as Predictors
Kyungmin Ahn, J. Derek Tucker, Wei Wu +1
Functional variables are often used as predictors in regression problems. A commonly-used parametric approach, called {\it scalar-on-function regression}, uses the $\ltwo$ inner pr…