  A critical question concerning generative networks applied to event
generation in particle physics is if the generated events add statistical
precision beyond the training sample. We show for a simple example with
increasing dimensionality how generative networks indeed amplify the training
statistics. We quantify their impact through an amplification factor or
equivalent numbers of sampled events.
