Bayesian experimental design (BED) provides a powerful and general framework for optimizing the design of experiments. However, its deployment often poses substantial computational challenges that can undermine its practical use. In this review, we outline how recent advances have transformed our ability to overcome these challenges and thus utilize BED effectively, before discussing some key areas for future development in the field.
翻译:Bayesian实验设计(BED)为优化实验设计提供了一个强大和总的框架,然而,它的部署往往带来巨大的计算挑战,可能损害其实际应用。 在本次审查中,我们概述了最近的进展如何改变了我们克服这些挑战的能力,从而有效地利用BED,然后才讨论该领域未来发展的一些关键领域。</s>