Deep probabilistic model synthesis enables unified modeling of whole-brain neural activity across individual subjects

ArXi:2603.14161v1 Announce Type: new Many disciplines need quantitative models that synthesize experimental data across multiple instances of the same general system. For example, neuroscientists must combine data from the brains of many individual animals to understand the species' brain in general. However, typical machine learning models treat one system instance at a time. Here we