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07/19/2023
Robust Bayesian Functional Principal Component Analysis
We develop a robust Bayesian functional principal component analysis (FP...
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06/01/2023
A Gaussian Sliding Windows Regression Model for Hydrological Inference
Statistical models are an essential tool to model, forecast and understa...
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03/11/2023
Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science
Scientists and statisticians often want to learn about the complex relat...
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08/18/2022
A Joint Estimation Approach to Sparse Additive Ordinary Differential Equations
Ordinary differential equations (ODEs) are widely used to characterize t...
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08/10/2022
Neural Networks for Scalar Input and Functional Output
The regression of a functional response on a set of scalar predictors ca...
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07/23/2022
Random Competing Risks Forests for Large Data
Random forests are a sensible non-parametric model to predict competing ...
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06/22/2022
Functional Nonlinear Learning
Using representations of functional data can be more convenient and bene...
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06/17/2022
Dynamical Modeling for non-Gaussian Data with High-dimensional Sparse Ordinary Differential Equations
Ordinary differential equations (ODE) have been widely used for modeling...
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05/30/2022
Automatic Search Interval for Smoothing Parameter in Penalized Splines
The selection of smoothing parameter is central to estimation of penaliz...
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01/18/2022
General P-splines for non-uniform B-splines
P-spline represents an unknown univariate function with uniform B-spline...
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04/08/2021
Functional L-Optimality Subsampling for Massive Data
Massive data bring the big challenges of memory and computation for anal...
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10/09/2020
Neural Networks as Functional Classifiers
In recent years, there has been considerable innovation in the world of ...
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09/18/2020
FuncNN: An R Package to Fit Deep Neural Networks Using Generalized Input Spaces
Neural networks have excelled at regression and classification problems ...
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06/17/2020
Deep Learning with Functional Inputs
We present a methodology for integrating functional data into deep dense...
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05/28/2019
Sparse Estimation of Historical Functional Linear Models with a Nested Group Bridge Approach
The conventional historical functional linear model relates the current ...
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01/01/2019
A Bayesian Spatial Model for Imaging Genetics
In recent work Greenlaw et al. (Bioinformatics, 2017) have developed a B...
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09/17/2018
Recovering the Underlying Trajectory from Sparse and Irregular Longitudinal Data
In this article, we consider the problem of recovering the underlying tr...
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09/13/2018
Estimating Historical Functional Linear Models with a Nested Group Bridge Approach
We study a scalar-on-function historical linear regression model which a...
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04/10/2015
