105 citations · 367 across the 30 of their papers we have counts for
5 papers · 1 filter
Log Gaussian Cox Process Background Modeling in High Energy Physics
Yuval Frid, Liron Barak, Pavani Jairam +2
Background modeling is one of the most critical components in high energy physics data analyses, and for smooth backgrounds it is often performed by fitting using an analytic funct…
Simulation-Prior Independent Neural Unfolding Procedure
Anja Butter, Theo Heimel, Nathan Huetsch +2
Machine learning allows unfolding high-dimensional spaces without binning at the LHC. The new SPINUP method extracts the unfolded distribution based on a neural network encoding th…
The Linear Collider Facility (LCF) at CERN
H. Abramowicz, E. Adli, F. Alharthi +406
In this paper we outline a proposal for a Linear Collider Facility as the next flagship project for CERN. It offers the opportunity for a timely, cost-effective and staged construc…
A Linear Collider Vision for the Future of Particle Physics
H. Abramowicz, E. Adli, F. Alharthi +446
In this paper we review the physics opportunities at linear colliders with a special focus on high centre-of-mass energies and beam polarisation, take a fresh look at the…
Fine-tuning machine-learned particle-flow reconstruction for new detector geometries in future colliders
Farouk Mokhtar, Joosep Pata, Dolores Garcia +4
We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross…