Statisticians and physicists team up to bring a machine learning approach to mining of nuclear data

Physicists use theoretical models to study physical quantities, such as the mass of nuclei, where they do not have experimental data. However, using a single imperfect theoretical model can lead to misleading results. To improve the quality of extrapolated predictions, scientists can instead use several different models and mix their results. In this way, scientists make the most of the collective wisdom of multiple models and obtain the best prediction from the most current experimental information.