Before revision: We introduce Deep Adaptive Design (DAD), a general method for amortizing the cost of performing sequential adaptive experiments using the framework of Bayesian optimal experimental design (BOED) . Traditional sequential BOED approaches require substantial computational time at each stage of the experiment.
After revision: We introduce Deep Adaptive Design (DAD), a general method for amortizing the cost of adaptive Bayesian experimental design that allows experiments to be run in real-time . Traditional sequential BOED approaches require substantial computational time at each stage of the experiment.