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Activity Number: 516
Type: Invited
Date/Time: Wednesday, August 3, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #318069 View Presentation
Title: Computational Enhancements to Bayesian Design of Experiments Using Gaussian Processes
Author(s): Brian Phillip Weaver*
Companies: Los Alamos National Laboratory
Keywords: Bayesian design of experiments ; Gaussian processes ; expected quantile improvement ; accelerated life tests ; designing computer experiments

Bayesian design of experiments is a methodology for incorporating prior information into the design phase of an experiment. Unfortunately, the typical Bayesian approach to designing experiments is both numerically and analytically intractable without additional assumptions or approximations. In this paper, we discuss how Gaussian processes can be used to help alleviate the numerical issues associated with Bayesian design of experiments. We provide an example based on accelerated life tests and compare our results with large-sample methods.

Authors who are presenting talks have a * after their name.

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