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PRODID:https://murmitoyen.com/events/vanille/udem/
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UID:69daabfeb77f8
DTSTAMP:20260411T161558
DTSTART:20180302T113000
SEQUENCE:0
TRANSP:OPAQUE
DTEND:20180302T123000
URL:https://murmitoyen.com/events/vanille/udem/detail/790385-deep-learning-
 in-high-energy-physics-amir-farbin-utexas-at-arlington
LOCATION:Université de Montréal - Pavillon Roger-Gaudry\, 2900\, chemin d
 e la Tour\, Montréal\, QC\, Canada\, H3T 1J6
SUMMARY:Deep learning in High Energy Physics - Amir Farbin (UTexas at Arlin
 gton)
DESCRIPTION:The recent Deep Learning (DL) renaissance has yielded impressiv
 e feats in industry and science\, replacing laborious feature engineering 
 with automatic feature learning\, providing better algorithms\, and enabli
 ng analysis of unlabeled data. DL is applicable to a large number of High 
 Energy Physics (HEP) problems such as tracking\, calorimetry\, particle id
 entification\, simulation\, monitoring\, anomaly detection\, noise reducti
 on\, data compression\, workflow optimization\, and data analysis. I will 
 discuss how DL can be applied to many of these areas and overview the firs
 t attempts of DL in HEP. I will also present several public datasets that 
 we have been compiling to enable collaborations with the Machine Learning 
 community and contributions from the public.
\nLa conférence est pour tou
 t public et le café est servi dès 11h30.
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