3 papers
cs.LG2025
Calibrated and uncertain? Evaluating uncertainty estimates in binary classification models
Aurora Grefsrud, Nello Blaser, Trygve Buanes
Rigorous statistical methods, including parameter estimation with accompanying uncertainties, underpin the validity of scientific discovery, especially in the natural sciences. Wit…
hep-ex2024
Precision calibration of calorimeter signals in the ATLAS experiment using an uncertainty-aware neural network
ATLAS Collaboration
The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of to…
hep-ph2023
Machine Learning Classification of Sphalerons and Black Holes at the LHC
Aurora Singstad Grefsrud, Trygve Buanes, Fotis Koutroulis +6
In models with large extra dimensions, "miniature" black holes (BHs) might be produced in high-energy proton-proton collisions at the Large Hadron Collider (LHC). In the semi-class…