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The authors of the discussed paper simplified the information-basedacquisition on estimating statistical expectation and developed analyticalcomputation for each involved quantity under uniform input distribution. Inthis discussion, we show that (1) the last three terms of the acquisitionalways add up to zero, leaving a concise form with a much more intuitiveinterpretation of the acquisition; (2) the analytical computation of theacquisition can be generalized to arbitrary input distribution, greatlybroadening the application of the developed framework.

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): 101404)