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Machine learning in high energy physics: a conversation over ice cream

5 October 2021
Europe/Zurich timezone

Contribution List

4 out of 4 displayed
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  1. 1. Introduction to machine learning in high energy physics
    Gregor Kasieczka (Hamburg University (DE))
    05/10/2021, 16:00
  2. 2. Graph neural networks
    Nikita Kazeev (Yandex School of Data Analysis (RU))
    05/10/2021, 16:25
  3. 3. Generative Models and Where to Find Them in HEP
    Michael Aaron Kagan (SLAC National Accelerator Laboratory (US))
    05/10/2021, 16:50
  4. 4. BDT, shallow and deep neural network techniques for analysis and detector reconstruction
    Gian Michele Innocenti (CERN)
    05/10/2021, 17:15