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VERSION:2.0
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BEGIN:VEVENT
SUMMARY:Machine learning with Gaia and large stellar surveys
DTSTART:20231109T143000Z
DTEND:20231109T160000Z
DTSTAMP:20260706T091216Z
UID:16448196-a558-4329-b827-89aac4a0070d
SEQUENCE:1
CREATED:20231103T114903Z
DESCRIPTION: ABSTRACT: The Gaia mission as well as large-scale ground-base
 d spectroscopic surveys are collecting complex data for millions (even bil
 lions) of stars. The community is therefore using more and more machine-le
 arning methods to cope with the amount of data. In this talk I will presen
 t some recent examples of supervised (typically regression) and unsupervis
 ed (typically dimensionality reduction and clustering) methods in the cont
 ext of stellar and Galactic astrophysics. In particular in the field of Ga
 lactic open clusters\, the combination of Gaia data with machine-learning 
 approaches is revolutionizing a whole field.  
LAST-MODIFIED:20231103T114903Z
LOCATION:Sala de Seminários do DF\,  Pavilhão de Física\, 2º piso
URL:http://df.vps.tecnico.ulisboa.pt/pt/eventos/machine-learning-with-gaia
 -and-large-stellar-surveys/
X-ALT-DESC;FMTTYPE=text/html:<p data-block-key="vjevp"> ABSTRACT: </p><p d
 ata-block-key="4jv3q">The Gaia mission as well as large-scale ground-based
  spectroscopic surveys are collecting complex data for millions (even bill
 ions) of stars. The community is therefore using more and more machine-lea
 rning methods to cope with the amount of data. <br/><br/>In this talk I wi
 ll present some recent examples of supervised (typically regression) and u
 nsupervised (typically dimensionality reduction and clustering) methods in
  the context of stellar and Galactic astrophysics. In particular in the fi
 eld of Galactic open clusters\, the combination of Gaia data with machine-
 learning approaches is revolutionizing a whole field.  </p>
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