Generation of nuclear data using Gaussian process regression

A new approach for generating nuclear data from experimental cross-section data is presented based on Gaussian process regression. This paper focuses on the generation of nuclear data for proton-induced nuclide production cross-sections with a nickel target. Our results provide reasonable regression curves and corresponding uncertainties and demonstrate that this approach is effective for generating nuclear data. Additionally, our results indicate that this approach can be applied in experimental design to reduce the uncertainty of generated nuclear data.