Bayesian optimization is an approach to optimizing objective functions that take a long time
(minutes or hours) to evaluate. It is best-suited for optimization over continuous domains of …

Bayesian experimental design (BED) provides a powerful and general framework for
optimizing the design of experiments. However, its deployment often poses substantial …

Computer simulation experiments are essential to modern scientific discovery, whether that
be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are …

Bayesian optimization is an approach to optimizing objective functions that take a long time
(minutes or hours) to evaluate. It is best suited for optimization over continuous domains of …

Automatic Chemical Design is a framework for generating novel molecules with optimized
properties. The original scheme, featuring Bayesian optimization over the latent space of a …

We report Phoenics, a probabilistic global optimization algorithm identifying the set of
conditions of an experimental or computational procedure which satisfies desired targets …

Abstract We introduce Deep Adaptive Design (DAD), a method for amortizing the cost of
adaptive Bayesian experimental design that allows experiments to be run in real-time …

Designing functional molecules and advanced materials requires complex design choices:
tuning continuous process parameters such as temperatures or flow rates, while …

The performance of acquisition functions for Bayesian optimisation to locate the global
optimum of continuous functions is investigated in terms of the Pareto front between …

We investigate the merits of replication, and provide methods for optimal design (including
replicates), with the goal of obtaining globally accurate emulation of noisy computer …