3 citations · 3 across the 3 of their papers we have counts for
3 papers
GNN-based track reconstruction for MUonE experiment
Damian Mizera, Mateusz Goncerz, Izabela Juszczak +3
A study of a Graph Neural Network-based model for track reconstruction in the context of MUonE experiment is presented, using simulated data corresponding to the test-run MUonE det…
Hybrid pattern recognition for charged particle tracking: Hough transform and convolutional neural efficiency networks
Carlo Varni, Krzysztof Ciesla, Marcin Wolter +3
Reconstructing charged-particle tracks in silicon detectors is a central task in high-energy physics experiments and a key component of both offline reconstruction and online event…
Machine learning based event reconstruction for the MUonE experiment
Milosz Zdybal, Marcin Kucharczyk, Marcin Wolter
A proof-of-concept solution based on the machine learning techniques has been implemented and tested within the MUonE experiment designed to search for New Physics in the sector of…