Bayesian experimental design is a tool for guiding experiments founded on the principle of expected information gain. I.e., which experiment design will inform the most about the model can be ...

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

A collaboration between scientists at Imperial College London and Swiss data analytics developer DataHow has created a new software function now available for Design of Experiment (DoE) for upstream ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 66, No. 2 (FEBRUARY 2017), pp. 363-386 (24 pages) Consumer products and services can often be described as mixtures of ...