Category: Bayesian Nonparametrics
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Bayesian Decision Theory for Gaussian Process (GP) Models with an Application Towards Approximate Evaluation of Source Functions Generating the GP as a Solution to a Differential Equation.
The author explores the integration of decision theory within the framework of Gaussian processes, focusing on nonparametric models. They highlight the relevance of selecting appropriate loss functions when applying Bayesian decision principles, particularly in the context of ordinary differential equations. Applications and future exploration in financial modeling and clustering are also suggested.