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Mixed-Stationary Gaussian Process for Flexible Non-Stationary Modeling of Spatial Outcomes
Different from a simple mixture of independent GPs, the mixture in stationarity allows the components to be spatial correlated, leading to improved prediction efficiency.
Functional Gaussian Process Model for Bayesian Nonparametric Analysis
Gaussian process is a theoretically appealing model for nonparametric analysis, but its computational cumbersomeness hinders its use in large scale and the existing reduced-rank solutions are usually heuristic.
Joint Hierarchical Gaussian Process Model with Application to Forecast in Medical Monitoring
Keyword: Extrapolation, Joint Model, Longitudinal Model, Hierarchical Gaussian Process, Cystic Fibrosis, Medical Monitoring
BET: Bayesian Ensemble Trees for Clustering and Prediction in Heterogeneous Data
We propose a novel "tree-averaging" model that utilizes the ensemble of classification and regression trees (CART).
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