In this article, we extend the Bayesian nonparametric regression method Gaussian Process Regression ... because of the large number of models it can represent. It allows classical statistical ...

have received a growing attention in statistics and machine learning as a powerful discrepancy measure for probability distributions. In this paper, we focus on forecasting a Gaussian process indexed ...

One such continuous function that be used for this task is the Gaussian Mixture Model (GMM). The probability density function of a general GMM is defined as ... Medical Imaging Meets Machine Learning ...

The present study utilizes two machine learning algorithms, namely, Genetic Programming (GP) and Gaussian Process Regression (GPR) models to approximate density dependent saltwater intrusion processes ...