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Dealing with Nuisance Parameters using Machine Learning in High Energy
  Physics: a Review

Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review

17 July 2020
T. Dorigo
P. D. Castro
ArXivPDFHTML

Papers citing "Dealing with Nuisance Parameters using Machine Learning in High Energy Physics: a Review"

4 / 4 papers shown
Title
Bridging Machine Learning and Sciences: Opportunities and Challenges
Bridging Machine Learning and Sciences: Opportunities and Challenges
Taoli Cheng
UQCV
OOD
AI4CE
27
2
0
24 Oct 2022
Bias and Priors in Machine Learning Calibrations for High Energy Physics
Bias and Priors in Machine Learning Calibrations for High Energy Physics
Rikab Gambhir
Benjamin Nachman
Jesse Thaler
AI4CE
34
7
0
10 May 2022
Machine Learning in the Search for New Fundamental Physics
Machine Learning in the Search for New Fundamental Physics
G. Karagiorgi
Gregor Kasieczka
S. Kravitz
Benjamin Nachman
David Shih
AI4CE
49
113
0
07 Dec 2021
A Living Review of Machine Learning for Particle Physics
A Living Review of Machine Learning for Particle Physics
Matthew Feickert
Benjamin Nachman
KELM
AI4CE
39
178
0
02 Feb 2021
1