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Abstract

Bayesian experimental design (BED) is a tool for guiding experiments founded on the principle of expected information gain. i.e., which experiment design will inform the most about the model can be predicted before experiments in a laboratory are conducted. BED is also useful when specific physical questions arise from the model which are answered from certain experiments but not from other experiments. BED can take two forms, and these two forms are expressed in three example models in this work.

Published in

arXiv

Citation

Walker, Eric A., and Kishore Ravisankar. “Bayesian Design of Experiments: Implementation, Validation and Application to Chemical Kinetics.” arXiv preprint arXiv:1909.03861 (2019).

arXiv:1909.03861

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