IML Machine Learning Working Group

Virtual (everywhere and nowhere)

Virtual (everywhere and nowhere)


Meeting will be by video only on Zoom.

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Meeting ID: 918 3662 6922
Password:  check email

Recording available at:

IML Machine Learning Working Group
Zoom Meeting ID
Simon Akar
Alternative hosts
Riccardo Torre, Fabio Catalano
Useful links
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Zoom URL
    • 3:00 PM 3:05 PM
      News 5m
      Speakers: Andrea Wulzer (CERN and EPFL), David Rousseau (LAL-Orsay, FR), Gian Michele Innocenti (CERN), Lorenzo Moneta (CERN), Loukas Gouskos (CERN), Dr Pietro Vischia (Universite Catholique de Louvain (UCL) (BE)), Riccardo Torre (CERN), Simon Akar (University of Cincinnati (US))
    • 3:05 PM 3:15 PM
      Introduction to workshop series on “AI in business” by CERN Knowledge Transfer 10m
      Speakers: CERN Knowledge Transfer, Paul Hientz
    • 3:15 PM 3:20 PM
      Question time 5m
    • 3:20 PM 3:45 PM
      FastCaloGAN: a tool for fast simulation of the ATLAS calorimeter system with Generative Adversarial Networks 25m
      Speaker: Michele Faucci Giannelli (INFN e Universita Roma Tor Vergata (IT))
    • 3:45 PM 3:50 PM
      Question time 5m
    • 3:50 PM 4:15 PM
      Pre-Learning a Geometry Using Machine Learning to Accelerate High Energy Physics Detector Simulations 25m
      Speaker: Evangelos Kourlitis (Argonne National Laboratory (US))
    • 4:15 PM 4:20 PM
      Question time 5m
    • 4:20 PM 4:45 PM
      High Fidelity Simulation of High Granularity Calorimeters with High Speed 25m
      Speakers: Engin Eren, Engin Eren (Deutsches Elektronen-Synchrotron DESY), Sascha Daniel Diefenbacher (Hamburg University (DE))
    • 4:45 PM 4:50 PM
      Question time 5m
    • 4:50 PM 5:15 PM
      Estimating Support Size of Distribution Learnt by Generative Adversarial Networks for Particle Detector Simulation 25m
      Speakers: Kristina Jaruskova (Czech Technical University in Prague), Kristina Jarůšková, Dr Sofia Vallecorsa (CERN)
    • 5:15 PM 5:20 PM
      Question time 5m
    • 5:20 PM 5:32 PM
      Sparse data from graph GANs 12m
      Speaker: Raghav Kansal (Univ. of California San Diego (US))
    • 5:32 PM 5:35 PM
      Question time 3m
    • 5:35 PM 5:47 PM
      Sparse data from Variational autoencoders 12m
      Speakers: Breno Orzari (UNESP - Universidade Estadual Paulista (BR)), Mary Touranakou (National and Kapodistrian University of Athens (GR))
    • 5:47 PM 5:50 PM
      Question time 3m