3 papers
hep-ex2025
Reconstructing hadronically decaying tau leptons with a jet foundation model
Laurits Tani, Joosep Pata, Joschka Birk
The limited availability and accuracy of simulated data has motivated the use of foundation models in high energy physics, with the idea to first train a task-agnostic model on lar…
hep-ph2025
OmniJet-: Learning point cloud calorimeter simulations using generative transformers
Joschka Birk, Frank Gaede, Anna Hallin +3
We show the first use of generative transformers for generating calorimeter showers as point clouds in a high-granularity calorimeter. Using the tokenizer and generative part of th…
hep-ph2024
Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics
Oz Amram, Luca Anzalone, Joschka Birk +7
Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrat…