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SUMMARY:Data-driven Discovery in the Time Domain -  Gautham Narayan (UIUC)
DTSTART:20191219T130000Z
DTEND:20191219T143000Z
UID:TALK136072@talks.cam.ac.uk
CONTACT:James Fergusson
DESCRIPTION:Optical surveys are probing our changing sky ever more efficie
 ntly\, with the Zwicky Transient Facility (ZTF) issuing a million alerts e
 very night. The volume\, and more importantly\, the rate of these alerts i
 s driving the community to using data science techniques for characterizat
 ion and categorization. I will describe how we are integrating these into 
 the ANTARES (https://antares.noao.edu/)\, operating on the real-time alert
  stream from ZTF. I will describe the infrastructure\, machine learning st
 ages and public interface\, and how you can use the system for time-domain
  discovery. But supervised machine learning techniques are only as good as
  their training sets\, which remain woefully biased and incomplete. I will
  describe the operations of the Young Supernova Experiment (YSE)\, and how
  we are using this survey to discover rare and unusual transients early to
  augment what we know about the time-domain sky to prepare us for the upco
 ming Large Synoptic Survey Telescope (LSST).
LOCATION:Kavli Large Meeting Room\, Kavli Building
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