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ML-based reweighting of BSM signal grids: an example in Rivet

Tomasz Procter · CERN

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About

Following on from discussions at previous reinterpretation forums on the reinterpretation of ML-based searches; we look at how one of these (ATLAS-SUSY-2018-30) has been used as a test-bed for studies of ML-based reweighting, which can reduce the computational load of studying large parameter spaces. Some new features of YODA 2 which allowed the project to run in Rivet will also be highlighted..

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The talk

  1. ML-based reweighting of BSM signal grids: an example in Rivet 2025-02-27 · 22 min · CERN's player

Credits and licence

Institution
CERN
Department
Workshops
Speaker
Tomasz Procter
Year
2025
Language
English
Subjects
Physics
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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