Modern Bayesian Experimental Design


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.

Statistical Science
Desi R. Ivanova
Desi R. Ivanova
Research Fellow in ML

Research Fellow @OxCSML. Former quant, former former gymnast.