The purpose is to maintain ISNET's mission of bringing the nuclear physics and statistical sciences communities together to report on the latest progress and to provide a vehicle for educating and enlightening the nuclear physics community in regard to the application of statistical methodologies that enable nuclear physics to reach more quantitatively rigorous scientific conclusions.
Topics: Uncertainty quantification and statistical analysis, Emulators and optimizations, Model mixing and data mining, Machine learning, Bayesian inference, Statistics techniques in nuclear experiments, New frontiers of nuclear physics