FALCON: Towards an Ultra Fast Non-parametric Detector Simulator

• Sergei Gleyzer (University of Florida (US))

Room: 13/2-005 Preliminary work towards a self-tuning non-parametric detector simulator that maps events at the generator level to reconstruction level.

Learning to generate with adversarial networks

• Gilles Louppe (New York University (US))

Room: 13/2-005 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.