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Implicit Quantile Neural Networks for Jet Simulation and Correction

2021-11-22Code Available0· sign in to hype

Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan

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Abstract

Reliable modeling of conditional densities is important for quantitative scientific fields such as particle physics. In domains outside physics, implicit quantile neural networks (IQN) have been shown to provide accurate models of conditional densities. We present a successful application of IQNs to jet simulation and correction using the tools and simulated data from the Compact Muon Solenoid (CMS) Open Data portal.

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