Nov 22 – 23, 2021
Europe/Zurich timezone

Session

Data preprocessing

Nov 22, 2021, 4:00 PM

Description

Which particle types and properties (energy, angle) are considered?
How large is the full sim dataset used to extract parametrization/train the network? Is the dataset balanced (is the number of events for the different particle properties almost the same?)
How the structure of the input data is defined (hits, cells, clusters, custom voxels,..)?
Which data structure is used for the ML training (1D vector, images, graphs..)?
Is input data scaled? How?
How do you store the preprocessed data?
How are the condition values for the ML training (energy of the particle, angle,..) encoded?

Presentation materials

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Saverio Mariani (Universita e INFN, Firenze (IT))
11/22/21, 4:00 PM

Session: Data preprocessing

Moritz Scham (Deutsches Elektronen-Synchrotron (DE))
11/22/21, 4:10 PM

Session: Data preprocessing

Michele Faucci Giannelli (INFN e Universita Roma Tor Vergata (IT))
11/22/21, 4:20 PM

Session: Data preprocessing

Jan Michal Dubinski (Warsaw University of Technology (PL))
11/22/21, 4:30 PM

Session: Data preprocessing

11/22/21, 4:40 PM
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