2 papers
hep-ph2020
Per-Object Systematics using Deep-Learned Calibration
Gregor Kasieczka, Michel Luchmann, Florian Otterpohl +1
We show how to treat systematic uncertainties using Bayesian deep networks for regression. First, we analyze how these networks separately trace statistical and systematic uncertai…
hep-ph2019
Deep-Learning Jets with Uncertainties and More
Sven Bollweg, Manuel Haussmann, Gregor Kasieczka +3
Bayesian neural networks allow us to keep track of uncertainties, for example in top tagging, by learning a tagger output together with an error band. We illustrate the main featur…