Generative Adversarial Networks (GAN) for compact beam source modelling in Monte Carlo simulations

no code implementations • 31 Jul 2019 • David Sarrut, Nils Krah, Jean-Michel Létang

The GAN is trained based on a phase space dataset to create a neural network, called Generator (G), allowing G to mimic the multidimensional data distribution of the phase space.

Generative Adversarial Network