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09/22/2022
Scalable Gaussian Process Hyperparameter Optimization via Coverage Regularization
Gaussian processes (GPs) are Bayesian non-parametric models popular in a...
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05/22/2022
Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation
Gaussian processes (GPs) are Bayesian non-parametric models useful in a ...
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04/29/2021
MuyGPs: Scalable Gaussian Process Hyperparameter Estimation Using Local Cross-Validation
Gaussian processes (GPs) are non-linear probabilistic models popular in ...
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04/17/2019
A comparison of statistical and machine learning methods for creating national daily maps of ambient PM_2.5 concentration
A typical problem in air pollution epidemiology is exposure assessment f...
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09/18/2018