Modern Bayesian Experimental Design
Modern Bayesian Experimental Design
Tom Rainforth,Adam Foster,Desi R. Ivanova,Freddie Bickford-Smith
2023 · DOI: 10.48550/arXiv.2302.14545
Statistical Science · 203 Citations
TLDR
It is outlined how recent advances have transformed the ability to overcome computational challenges and thus utilize BED effectively, before discussing some key areas for future development in the field.
Abstract
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.