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VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Neural Networks for Scientific Data Analysis in Particle Physics
DTSTART:20270310T090000Z
DTEND:20270310T160000Z
DTSTAMP:20261022T110400Z
UID:indico-event-19406@indico.global
DESCRIPTION:Speakers: Artemiy Belousov\n\nDescription\nThis one-day hands-
 on workshop introduces the fundamental concepts of neural networks\, with 
 a focus on convolutional neural networks (CNNs)\, and their application to
  scientific data. Examples come from modern analysis workflows of the CBM 
 experiment\, where CNNs are used to classify heavy-ion collision events an
 d identify signatures of quark–gluon plasma formation.\nParticipants wil
 l learn how to prepare scientific datasets for machine learning and how to
  train and validate models on simulated data generated with transport mode
 ls such as PHSD. They will then apply trained networks to realistic detect
 or data and learn how to evaluate and interpret model performance.\nThe wo
 rkshop builds on "Monte Carlo Simulation and Data Analysis with ROOT in Pa
 rticle Physics" (March 9). Participation in that workshop is strongly reco
 mmended\, as its datasets and analysis concepts serve as the starting poin
 t here.\nLearning Goals\nParticipants will learn how to:\n\nUnderstand neu
 ral network architectures\, including CNNs\nPrepare scientific datasets fo
 r machine learning\nTrain and validate CNN models\nApply machine learning 
 methods to detector and simulation data\n\nProgram\nMorning\n\nIntroductio
 n to machine learning in particle physics\nFundamentals of neural networks
 \nConvolutional neural networks (CNNs)\nDataset preparation and feature en
 gineering\n\nAfternoon\n\nCNN training and validation\nEvent classificatio
 n examples from CBM\nPerformance evaluation and interpretation\nHands-on M
 L exercises\n\nTarget audience: Students and researchers interested in app
 lying machine learning to scientific data. Basic Python experience is requ
 ired. Prior attendance of Workshop 1 or equivalent familiarity with simula
 tion and detector data is recommended.\n\nhttps://indico.global/event/1940
 6/
LOCATION:N260/3.13
URL:https://indico.global/event/19406/
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END:VCALENDAR