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SUMMARY:Real-time ML-powered transient discovery with GOTO and Kilonova Se
 ekers  - Tom Killestein (Warwick)
DTSTART:20250814T150000Z
DTEND:20250814T160000Z
UID:TALK235087@talks.cam.ac.uk
CONTACT:65128
DESCRIPTION:With the advent of modern transient surveys and the upcoming R
 ubin Observatory soon to start full operations\, time-domain astronomy has
  firmly entered its era of big data\, and has moved into a domain where we
  are flooded with novel transient discoveries rather than artifacts\, than
 ks to machine learning methods. Prioritisation of finite follow-up resourc
 es and early classification of objects are crucial to make the most of thi
 s.\n\nIn this talk I will discuss the ongoing development of high-performa
 nce deep learning classifiers and contextual classification algorithms for
  the Gravitational-wave Optical Transient Observer (GOTO) -- an all-sky op
 tical transient survey built specifically for real-time follow-up of gravi
 tational wave (GW) events. I will also discuss Kilonova Seekers\, a citize
 n science project hosted on Zooniverse which shows data from GOTO to membe
 rs of the public in real time - uniquely enabling them to join the search 
 for GW counterparts\, and make impactful scientific discoveries in the pro
 cess\, whilst also delivering vital data for real-time adaptive classifier
 s and active learning.
LOCATION:Martin Ryle Seminar Room\, KICC
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