VSPsnap is a collection of R and Python code for Gaussian Process regression in a kriging-like setting (i.e. two features (X,Y) and a target (Z)) - with a focus on SARS-CoV2 data (genomic/IR/FR).
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Updated
Jun 3, 2023 - R
VSPsnap is a collection of R and Python code for Gaussian Process regression in a kriging-like setting (i.e. two features (X,Y) and a target (Z)) - with a focus on SARS-CoV2 data (genomic/IR/FR).
Companion R code for the book Bayesian Optimization with Application to Computer Experiments
This repository is out of date. See instead: https://github.com/paigejo/ELK
This instruction aims to reproduce the results in the paper “Mesh-clustered Gaussian process emulator for partial differential equation boundary value problems”(2024) to appear in Technometrics.
Power Link Functions in Modeling Dependent Ordinal Data
Missing data imputation for longitudinal multi-variable EHR data. Paper in JAMIA.
Simple Gaussian process in R.
AvGPR is a package that calculates a weighted average Gaussian Process regression model over 5 implementations from packages in both R and Python.
Gaussian Process Inference
This R package allows the estimation and prediction for a clustered Gaussian process model proposed by Sung, Haaland, Hwang, and Lu (2023) in Statistica Sinica
Radial neighbors GP
Gaussian processes for machine learning in R and FORTRAN.
This instruction aims to reproduce the results in the paper “Functional-Input Gaussian Processes with Applications to Inverse Scattering Problems” proposed by Sung, Wang, Cakoni, Harris, and Hung.
Fast Gaussian Processes in R with GPUs and Vecchia Approximation
R package for Partially Separable Multivariate Functional Data and Functional Graphical Models
Code for reproducing the results of the paper "A class of modular and flexible covariate-based covariance functions for nonstationary spatial modeling"
R package for nonstationary spatial modeling with covariate-based covariance functions
Gaussian Process Approximations for Designed Experiments
Trendiness analysis of Danish COVID-19 data
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