4 citations · 5 across the 2 of their papers we have counts for
3 papers
hep-ex2026
How to scale your HEP ML models: A recipe for robust architecture comparisons at scale
Matthias Vigl, Nikita Pond, Jackson Barr +5
Much of the recent progress in machine learning domains such as language models has come from scaling laws that predict performance as a function of training effort. In high-energy…
hep-ex2024★ 1 cited
Transformers for Charged Particle Track Reconstruction in High Energy Physics
Samuel Van Stroud, Philippa Duckett, Max Hart +4
Reconstructing charged particle tracks is a fundamental task in modern collider experiments. The unprecedented particle multiplicities expected at the High-Luminosity Large Hadron…
hep-ex2023★ 4 cited
Secondary Vertex Reconstruction with MaskFormers
Samuel Van Stroud, Nikita Pond, Max Hart +4
In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by - or -…