New simulation strategies are evolving next to full and "fast" simulation. This session will cover two examples. The discussion will cover how these future strategies could help with physicists' simulation needs.
FALCON: Towards an Ultra Fast Non-parametric Detector Simulator30m
Preliminary work towards a self-tuning non-parametric detector simulator that maps events at the generator level to reconstruction level.
(University of Florida (US))
In this talk, we introduce generative adversarial networks (Goodfellow, 2014), a machine learning framework for building generative models through an adversarial learning process. Inspired from its recent success to model and generate natural images, we then explore and discuss how this framework could be used as a way to generate physics data.