Boukouvalas, Alexis, Cornford, Dan and Stehlik, Milan (2009). Approximately optimal experimental design for heteroscedastic Gaussian process models. Technical Report. Aston University, Birmingham. (Unpublished)
Abstract
This paper presents a greedy Bayesian experimental design criterion for heteroscedastic Gaussian process models. The criterion is based on the Fisher information and is optimal in the sense of minimizing parameter uncertainty for likelihood based estimators. We demonstrate the validity of the criterion under different noise regimes and present experimental results from a rabies simulator to demonstrate the effectiveness of the resulting approximately optimal designs.
Divisions: | ?? 50811700Jl ?? College of Engineering & Physical Sciences > Systems analytics research institute (SARI) College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies |
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Uncontrolled Keywords: | Gaussian process,emulation,experimental design |
ISBN: | 14 | PURE Output Type: | Technical report |
Published Date: | 2009-11-10 |
Authors: |
Boukouvalas, Alexis
Cornford, Dan ( ![]() Stehlik, Milan |