Machine Learning and generative modeling in particle physics analysis and simulation |
Contacts
To get in touch with the particles team, please contact Frank Gaede
Team Members
Related projects
Recent publications
- Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows: Thorsten Buss et al., arXiv, doi: 10.48550/arXiv.2405.20407
- OmniJet-$α$: The first cross-task foundation model for particle physics: Joschka Birk et al., arXiv, doi: 10.48550/arXiv.2403.05618
- CaloPointFlow II Generating Calorimeter Showers as Point Clouds: Simon Schnake et al., arXiv, doi: 10.48550/arXiv.2403.15782
- CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation: Erik Buhmann et al., arXiv, doi: 10.48550/arXiv.2305.04847
- AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization: Sebastian Bieringer et al., arXiv, doi: 10.48550/arXiv.2312.14027