Estimating cosmological parameters from the dark matter distribution

33rd International Conference on Machine Learning, ICML 2016

Volumn 5, Issue , 2016, Pages 3584-3594

  Ravanbakhsh, Siamak ^a   Oliva, Junier ^a   Fromenteau, Sebastien ^b   Price, Layne C ^b   Ho, Shirley ^b   Schneider, Jeff ^a   Póczos, Barnabas ^a  

^a Carnegie Mellon University ^*  (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COSMIC RAY MEASUREMENT; COSMOLOGY; GALAXIES; LEARNING SYSTEMS; MAXIMUM LIKELIHOOD; THREE DIMENSIONAL COMPUTER GRAPHICS;

CONVOLUTIONAL NETWORKS; CORRELATION FUNCTION; COSMOLOGICAL MODELS; COSMOLOGICAL PARAMETERS; LARGE SCALE STRUCTURES; MACHINE LEARNING TECHNIQUES; THREE DIMENSIONS; VOLUMETRIC REPRESENTATION;

PARAMETER ESTIMATION;

EID: 84998842231     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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