IML Machine Learning Working Group: unfolding

Thursday 27 Jul 2023, 15:00 → 18:00 Europe/Zurich

Virtual

Topic: unfolding

Recording_IML_Meeting_Unfolding_270723.mp4

15:00 → 15:05 News

Speakers: Anja Butter (Centre National de la Recherche Scientifique (FR)), Fabio Catalano (CERN), Julian Garcia Pardinas (CERN), Lorenzo Moneta (CERN), Michael Kagan (SLAC National Accelerator Laboratory (US)), Dr Pietro Vischia (Universidad de Oviedo and Instituto de Ciencias y Tecnologías Espaciales de Asturias (ICTEA)), Simon Akar (University of Cincinnati (US)), Stefano Carrazza (CERN)

15:05 → 15:35 Unfolding and machine learning: introduction

Speaker: Bogdan Malaescu (LPNHE-Paris CNRS/IN2P3 (FR))

IML_UnfoldingIntro_Malaescu.pdf

15:35 → 15:45 Question time

15:45 → 16:15 Biases and pitfalls in unfolding

Speaker: Igor Volobouev (Texas Tech University (US))

unfolding_pitfalls.pdf

16:15 → 16:25 Discussion

16:25 → 16:40 ν2-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows

https://arxiv.org/abs/2307.02405
Available time may be extended depending on the number of additional contributions.

Speaker: Mr Matthew Leigh (University of Geneva)

nuFlows talk 27-07-22.pdf

16:40 → 16:45 Discussion

16:45 → 17:00 ML Unfolding based on conditional Invertible Neural Networks using Iterative Training

https://arxiv.org/abs/2212.08674

Speaker: Mathias Josef Backes (Heidelberg University (DE))

IML_unfolding_mBackes.pdf

17:00 → 17:05 Discussion