Machine Learning for neutron source distributions

ArXi:2605.12165v1 Announce Type: cross In light of the recent advancements in machine learning, we propose a novel approach to neutron source distribution estimation through the utilisation of probabilistic generative models. The estimation is based on a Monte Carlo particle list, which is only required during the