Celeste: Variational inference for a generative model of astronomical images

32nd International Conference on Machine Learning, ICML 2015

Volumn 3, Issue , 2015, Pages 2095-2103

  Regier, Jeffrey ^a   Miller, Andrew ^b   McAuliffe, Jon ^a   Adams, Ryan ^b   Hoffman, Matt ^c   Lang, Dustin ^d   Schlegel, David ^e   Prabhat, ^e  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b HARVARD UNIVERSITY   (United States)

^c ADOBE Systems India Private Limited   (India)

^d CARNEGIE MELLON UNIVERSITY   (United States)

^e LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

ASTRONOMICAL IMAGES; CELESTIAL BODIES; PIXEL INTENSITIES; POISSON RANDOM VARIABLES; PRIOR DISTRIBUTION; STATE-OF-THE-ART METHODS; SYNTHETIC IMAGES; VARIATIONAL INFERENCE;

LEARNING SYSTEMS;

EID: 84970028519     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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