1.2k citations · 29.3k across the 390 of their papers we have counts for
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astro-ph.IM2013★ 119 cited
SOMz: photometric redshift PDFs with self organizing maps and random atlas
M. Carrasco Kind, R. J. Brunner
In this paper we explore the applicability of the unsupervised machine learning technique of Self Organizing Maps (SOM) to estimate galaxy photometric redshift probability density…
astro-ph.CO2013★ 97 cited
Spectroscopic Needs for Imaging Dark Energy Experiments: Photometric Redshift Training and Calibration
J. Newman, A. Abate, F. Abdalla +58
Large sets of objects with spectroscopic redshift measurements will be needed for imaging dark energy experiments to achieve their full potential, serving two goals:_training_, i.e…
astro-ph.CO2013★ 272 cited
TPZ : Photometric redshift PDFs and ancillary information by using prediction trees and random forests
M. Carrasco Kind, R. J. Brunner
With the growth of large photometric surveys, accurately estimating photometric redshifts, preferably as a probability density function (PDF), and fully understanding the implicit…