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VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
BEGIN:VEVENT
SEQUENCE:2
UID:UW-Physics-Event-5930
DTSTART:20200715T170000Z
DURATION:PT1H0M0S
DTSTAMP:20260415T023623Z
LAST-MODIFIED:20200713T144523Z
LOCATION:
SUMMARY:String data and machine learning \, Physics ∩ ML Seminar\, A
 ndre Lukas\,  University of Oxford
DESCRIPTION:Recently\, string theorists have started to use machine le
 arning techniques. I will explain why string theory might be an intere
 sting arena for modern computational methods and discuss two specific 
 applications of machine learning to problems which arise in the contex
 t of string model building. In the first part\, I will show how machin
 e learning can help understand certain mathematical structures\, speci
 fically the cohomology of line bundles on complex manifolds. In the se
 cond part\, machine learning is applied to a data set of string standa
 rd models.
URL:https://www.physics.wisc.edu/events/?id=5930
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