Speaker
Raymundo Ramos
(KIAS)
Description
In this talk we discuss a proposal where a neural network is trained to classify regions in multidimensional parameter space according to a function that determines their importance. These regions in general can have complicated shapes and disconnected subregions. Accurate classification of regions of importance with a neural network can improve event generation and Monte Carlo integration, specially for costly time consuming calculations.
Primary author
Raymundo Ramos
(KIAS)
