240 citations · 1.2k across the 35 of their papers we have counts for
35 papers
GPT-like transformer model for silicon tracking detector simulation
Tadej Novak, Borut Paul Kerševan
Simulating physics processes and detector responses is essential in high energy physics and represents significant computing costs. Generative machine learning has been demonstrate…
Physics Briefing Book: Input for the 2026 update of the European Strategy for Particle Physics
Jorge de Blas, Monica Dunford, Emanuele Bagnaschi +127
The European Strategy for Particle Physics (ESPP) reflects the vision and presents concrete plans of the European particle physics community for advancing human knowledge in fundam…
Neural Fake Factor Estimation Using Data-Based Inference
Jan Gavranovič, Lara Čalić, Jernej Debevc +2
In a high-energy physics data analysis, the term "fake" backgrounds refers to events that would formally not satisfy the (signal) process selection criteria, but are accepted nonet…
Systematic Evaluation of Generative Machine Learning Capability to Simulate Distributions of Observables at the Large Hadron Collider
Jan Gavranovič, Borut Paul Kerševan
Monte Carlo simulations are a crucial component when analysing the Standard Model and New physics processes at the Large Hadron Collider. This paper aims to explore the performance…
Comparing Traditional and Deep-Learning Techniques of Kinematic Reconstruction for polarisation Discrimination in Vector Boson Scattering
M. Grossi, J. Novak, B. Kersevan +1
Measuring longitudinally polarised vector boson scattering in WW channel is a promising way to investigate unitarity restoration with the Higgs mechanism and to search for possible…
VBSCan Mid-Term Scientific Meeting
Julien Baglio, Alessandro Ballestrero, Riccardo Bellan +48
This document summarises the talks and discussions happened during the VBSCan Mid-Term Scientific Meeting workshop. The VBSCan COST action is dedicated to the coordinated study of…