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SUMMARY:Transforming Particle Physics with Machine Learning
DTSTART:20260528T141500Z
DTEND:20260528T153000Z
DTSTAMP:20260511T080000Z
UID:indico-event-5832@agenda.irmp.ucl.ac.be
DESCRIPTION:Speakers: Tilmann Plehn (University of Heidelberg)\n\nProgram:
 16:15 Colloquium talk by Tilman Plehn17:15 Open Q&A session17:30 Drinks & 
 Snacks with the speaker in the Cyclofette\nAbstract:Machine learning is no
 t only transforming our lives\, but also the way we do (particle) physics.
  I will describe a few key aspects of ML applications in particle physics\
 , defining something like physics-specific representation learning. I will
  then give examples how we can use learned representations to improve netw
 ork performance\, include networks in a statistical framework\, and unders
 tand what they learn. Finally\, I will briefly show how an agentic interfa
 ce to ML-simulations re-defines the way we do numerical simulations.\n\nht
 tps://agenda.irmp.ucl.ac.be/event/5832/
LOCATION:CYCL01 (Marc de Hemptinne (chemin du Cyclotron\, 2\, Louvain-la-N
 euve))
URL:https://agenda.irmp.ucl.ac.be/event/5832/
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