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Learning to Discover

19–29 avr. 2022
Institut Pascal
Fuseau horaire Europe/Paris

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Session

Generative Models workshop

GEN
25 avr. 2022, 09:00
Institut Pascal

Institut Pascal

Présidents de session

Generative Models workshop: Monday morning

  • Il n'a pas de président de session pour ce bloc

Generative Models workshop: Monday afternoon

  • Cécile Germain (LISN, Université Paris-Saclay)

Generative Models workshop: Tuesday morning

  • Il n'a pas de président de session pour ce bloc

Generative Models workshop: Tuesday afternoon

  • Il n'a pas de président de session pour ce bloc

Documents de présentation

Aucun document.

  1. 65. Generator Workshop introduction
    25/04/2022 09:00
  2. 66. Overview of generator model for detector simulation
    Johnny Raine (Université de Genève)
    25/04/2022 09:15

    Detailed simulations of physics processes are a cornerstone of most physics measurements and searches at experiments such as those at the Large Hadron Collider (LHC) as well as in other scientific domains. However, the large volumes of data collected at the LHC precludes a requirement for even more simulated data in order to test various hypotheses to a high precision. As the LHC moves to the...

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  3. 95. Generator model for 4-momenta events
    Sascha Diefenbacher (Universität Hamburg)
    25/04/2022 10:40

    Event generation and Hadronization make up a significant fraction of our high energy physics simulation chain. Therefore there exists a strong interest in using generative models to supplement these simulation tasks. In both applications the data is commonly expressed as a list of 4-momenta. This presents an additional challenge to any generative model, as 4-momenta have inherent complex...

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  4. 93. Break out session in the small amphi
    25/04/2022 11:30
  5. 94. GNNs for generating molecules and PDE solutions
    Max Welling (U. Amsterdam / MSR)
    25/04/2022 14:00

    Graph Neural Networks (GNNs) have proven to be a versatile tool to predict properties of molecules, generative molecules and even predict solutions of a partial differential equation (PDE). Many physical application domains also exhibit symmetries which can be incorporated into the GNNs through equivariant convolutions or data augmentation. In this talk I will explain how this tool can be...

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  6. 69. Breakout sessions
    25/04/2022 16:00
  7. 67. The calorimeter challenge and ODD detector
    Anna Zaborowska (CERN)
    26/04/2022 09:00

    There has been many recent developments in the application of machine-learning techniques to fast simulation of cascades in the calorimeters. This is usually the most time consuming part of the event simulation in high energy physics experiments. Most current efforts are focused and fine tuned to specific detectors, which makes it difficult to compare. We present a first fast calorimeter...

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  8. 71. Breakout sessions
    26/04/2022 11:00
  9. 98. Meta-learning for fast simulation of multiple calorimeter responses
    Dalila Salamani (CERN)
    26/04/2022 14:00

    In LHC experiments, the calorimeter is a key detector technology to measure the energy of particles. These particles interact electromagnetically and/or hadronically with the material of the calorimeter, creating cascades of secondary particles or showers. Describing the showering process relies on simulation methods that precisely describe all particle interactions with matter. Constrained by...

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  10. 72. Breakout sessions
    26/04/2022 14:20
  11. 70. Breakout sessions
  12. 68. Breakout sessions
  13. 73. Conclusion from breakout sessions
Ordre du jour en construction...