Discussion: 'Bayesian Optimal Design of Experiments for Inferring the Statistical Expectation of Expensive Black-Box Functions' (Pandita, P., Bilionis, I., and Panchal, J., 2019, ASME J. Mech. Des., 141(10), p. 101404)

Autor:	Yulin Pan, Xianliang Gong
Rok vydání:	2021
Předmět:	Distribution (number theory) Mechanics of Materials Bayesian optimal design Mechanical Engineering Computation Black box Zero (complex analysis) Applied mathematics Computer Graphics and Computer-Aided Design Computer Science Applications Interpretation (model theory) Mathematics
Zdroj:	Journal of Mechanical Design. 144
ISSN:	1528-9001 1050-0472
DOI:	10.1115/1.4053112
Popis:	The authors of the discussed paper simplified the information-based acquisition on estimating statistical expectation and developed analytical computation for each involved quantity under uniform input distribution. In this discussion, we show that (1) the last three terms of the acquisition always add up to zero, leaving a concise form with a much more intuitive interpretation of the acquisition; (2) the analytical computation of the acquisition can be generalized to arbitrary input distribution, greatly broadening the application of the developed framework.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::70450cf9bcd158a5a27a6fd870d46da7 https://doi.org/10.1115/1.4053112 Zobrazit plný text záznamu