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A Cautionary Tale of Decorrelating Theory Uncertainties

A Cautionary Tale of Decorrelating Theory Uncertainties

16 September 2021
A. Ghosh
Benjamin Nachman
ArXivPDFHTML

Papers citing "A Cautionary Tale of Decorrelating Theory Uncertainties"

7 / 7 papers shown
Title
FAIR Universe HiggsML Uncertainty Challenge Competition
FAIR Universe HiggsML Uncertainty Challenge Competition
W. Bhimji
P. Calafiura
Ragansu Chakkappai
Yuan-Tang Chou
S. Diefenbacher
...
D. Rousseau
Benjamin Sluijter
Benjamin Thorne
Ihsan Ullah
Yulei Zhang
32
2
0
03 Oct 2024
New Metric Formulas that Include Measurement Errors in Machine Learning
  for Natural Sciences
New Metric Formulas that Include Measurement Errors in Machine Learning for Natural Sciences
Umberto Michelucci
F. Venturini
13
4
0
30 Sep 2022
Interpretable Uncertainty Quantification in AI for HEP
Interpretable Uncertainty Quantification in AI for HEP
Thomas Y. Chen
B. Dey
A. Ghosh
Michael Kagan
Brian D. Nord
Nesar Ramachandra
25
7
0
05 Aug 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
20
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
31
113
0
07 Dec 2021
Online-compatible Unsupervised Non-resonant Anomaly Detection
Online-compatible Unsupervised Non-resonant Anomaly Detection
Vinicius Mikuni
Benjamin Nachman
David Shih
14
35
0
11 Nov 2021
Measuring and testing dependence by correlation of distances
Measuring and testing dependence by correlation of distances
G. Székely
Maria L. Rizzo
N. K. Bakirov
175
2,577
0
28 Mar 2008
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