Cross-Domain Transfer with Particle Physics Foundation Models: From Jets to Neutrino Interactions
hep-ex, cs.LG, hep-ph, physics.data-an
Submitted: 2026-04-14
Updated: 2026-08-25
Code: https://github.com/gregorkrz/minerva-ml
Terminology
Sources
- A Living Review of Machine Learning for Particle Physics
- OmniJet-$\alpha$: The first cross-task foundation model for particle physics
- Solving Key Challenges in Collider Physics with Foundation Models
- Foundation models for high-energy physics
- Re-Simulation-based Self-Supervised Learning for Pre-Training Foundation Models
- Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models
- Is Tokenization Needed for Masked Particle Modelling?
- HEP-JEPA: A foundation model for collider physics using joint embedding predictive architecture
- A Method to Simultaneously Facilitate All Jet Physics Tasks
- FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics
- Particle Trajectory Representation Learning with Masked Point Modeling
- Panda: Self-distillation of Reusable Sensor-level Representations for High Energy Physics
- OmniCosmos: Transferring Particle Physics Knowledge Across the Cosmos
- OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers
- From eV to EeV: Neutrino Cross Sections Across Energy Scales
- Progress and open questions in the physics of neutrino cross sections
- Neutrino Interactions with Nucleons and Nuclei: Importance for Long-Baseline Experiments
- Neutrino-Nucleus Cross Sections for Oscillation Experiments
- NuSTEC White Paper: Status and Challenges of Neutrino-Nucleus Scattering
- Progress in measurements of 0.1--10 GeV neutrino-nucleus scattering and anticipated results from future experiments