BEGIN:VCALENDAR
VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
BEGIN:VEVENT
SEQUENCE:1
UID:UW-Physics-Event-6860
DTSTART:20220209T170000Z
DTEND:20220209T180000Z
DTSTAMP:20260414T154051Z
LAST-MODIFIED:20220207T203211Z
LOCATION:5280 Chamberlin
SUMMARY:Probabilistic Deep Learning and Applications to FRB parameter 
 inference\, Physics ∩ ML Seminar
DESCRIPTION:Probabilistic Deep Learning is a powerful tool that combin
 es predictive power of deep learning algorithms with rigorous statisti
 cal methods for inferring complex relations in stochastic data. The ta
 lk will first give an introduction to probabilistic DL with review of 
 the most popular frameworks\, and then an application of presented met
 hods to the inference of properties of Fast Radio Bursts.
URL:https://www.physics.wisc.edu/events/?id=6860
END:VEVENT
END:VCALENDAR