Tag: Probability
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Kernel-Embedded Gaussian Processes for Bayesian Computation and Model Evaluation
(Work in Progress) It had been a while since I had worked on a technical blog post, so I wanted to get something out there. I have been playing around with a lot of concepts in my head centering on Gaussian processes and using them for Bayesian computation. Most of the time when I write…
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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.