97 citations · 312 across the 12 of their papers we have counts for
3 papers · 1 filter
Understanding Event-Generation Networks via Uncertainties
Marco Bellagente, Manuel Haußmann, Michel Luchmann +1
Following the growing success of generative neural networks in LHC simulations, the crucial question is how to control the networks and assign uncertainties to their event output.…
Invertible Networks or Partons to Detector and Back Again
Marco Bellagente, Anja Butter, Gregor Kasieczka +5
For simulations where the forward and the inverse directions have a physics meaning, invertible neural networks are especially useful. A conditional INN can invert a detector simul…
How to GAN away Detector Effects
Marco Bellagente, Anja Butter, Gregor Kasieczka +2
LHC analyses directly comparing data and simulated events bear the danger of using first-principle predictions only as a black-box part of event simulation. We show how simulations…