GPz: Non-stationary sparse Gaussian processes for heteroscedastic uncertainty estimation in photometric redshifts
The next generation of cosmology experiments will be required to use photometric redshifts rather than spectroscopic redshifts. Obtaining accurate and well-characterized photometric redshift distributions is therefore critical for Euclid, the Large Synoptic Survey Telescope and the Square Kilometre...
Hlavní autoři: | Almosallam, I, Jarvis, M, Roberts, S |
---|---|
Médium: | Journal article |
Vydáno: |
Oxford University Press
2016
|
Podobné jednotky
-
GPz: non-stationary sparse Gaussian processes for heteroscedastic uncertainty estimation in photometric redshifts
Autor: Almosallam, I, a další
Vydáno: (2016) -
Improving Photometric Redshift Estimation using GPz: size information,
post processing and improved photometry
Autor: Gomes, Z, a další
Vydáno: (2017) -
A Sparse Gaussian Process Framework for Photometric Redshift Estimation
Autor: Almosallam, I, a další
Vydáno: (2015) -
Augmenting machine learning photometric redshifts with Gaussian mixture models
Autor: Hatfield, PW, a další
Vydáno: (2020) -
Photometric redshift estimation using Gaussian processes
Autor: Bonfield, D, a další
Vydáno: (2010)