Speaker
Henry Day-Hall
(DESY)
Description
Physics employs careful factorising of effects to make powerful general predictions. In a Mixture of Experts network, well chosen factorisation of knowledge can improve both memory footprint and generalisation.
This work explores the relative merits of Expert networks, in comparison to equivalent generalist models. In the setting of fast generative calorimeter simulation, both architectures are explored and the strengths illustrated.
Author
Henry Day-Hall
(DESY)