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DTSTART:20240101T000000
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DTSTART;TZID=UTC:20240618T160000
DTEND;TZID=UTC:20240618T170000
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SUMMARY:Speaker: David Miller (University of Chicago) - Title: Black Boxes or Interpretable Models? Applications of Machine Learning\, Symmetries\, and Domain Knowledge to High-Dimensional Problems in Particle Physics.
DESCRIPTION:Research Progress Meeting \nDate: June 18\, 2024 \nTime: 4:00- 5:00 pm  \nLocation: Sessler Conference Room- 50A-5132 [In-Person and HYBRID]  \nSpeaker: David Miller (University of Chicago) \nTitle: Black Boxes or Interpretable Models? Applications of Machine Learning\, Symmetries\, and Domain Knowledge to High-Dimensional Problems in Particle Physics. \nAbstract: The world of artificial intelligence (AI) and machine learning (ML) has undergone what some scientists refer to as the “3rd Age of AI” due to the confluence of developments in Algorithms\, Computing Resources\, and Big Data. Particle Physics has benefitted from\, and in many ways strengthened and advanced\, progress in AI/ML for decades due to its proliferation of enormous data sets\, complex instrumentation\, and enormous computing infrastructure. However\, there exist both known and unknown deficiencies in our ability to explain “why” some AI/ML models yield a certain result. In this talk\, I will discuss some of the context and applications of AI/ML in experimental particle physics. I will then focus on a few projects ongoing in my group that we believe target important problems relevant to the use of machine learning\, symmetries\, and domain knowledge in particle physics. \n\nJoin Zoom Meeting\nhttps://lbnl.zoom.us/j/95679892182?pwd=RU5xU2dDRFNabnR1U3pQMklkYWFIdz09 \nMeeting ID: 956 7989 2182 \nPasscode: 169037
URL:https://rpm.physics.lbl.gov/event/speaker-david-miller-university-of-chicago-title-a-new-paradigm-for-axion-discovery-from-broadband-direct-detection-to-collider-interpretations/
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