Speaker
Davide Lancierini
(Universitaet Zuerich (CH))
Description
Please, visit (and apply for!) the separate page for this tutorial: https://indico.cern.ch/event/973553/
Generative Adversarial Networks (GANs) play a key role in the development of fast simulation methods in High Energy Physics. In this workshop we will explore the applications of Conditional GANs and pix2pix GANs to a toy dataset. In particular we will implement common methods to avoid mode collapse phenomena.
The workshop will follow a "code-along" approach with space for discussion on code implementation and performance of GANs in tackling fast simulation problems.
