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...
Huvudupphovsmän: | Almosallam, I, Jarvis, M, Roberts, S |
---|---|
Materialtyp: | Journal article |
Publicerad: |
Oxford University Press
2016
|
Liknande verk
Liknande verk
-
GPz: Non-stationary sparse Gaussian processes for heteroscedastic uncertainty estimation in photometric redshifts
av: Almosallam, I, et al.
Publicerad: (2016) -
Improving Photometric Redshift Estimation using GPz: size information,
post processing and improved photometry
av: Gomes, Z, et al.
Publicerad: (2017) -
A Sparse Gaussian Process Framework for Photometric Redshift Estimation
av: Almosallam, I, et al.
Publicerad: (2015) -
Augmenting machine learning photometric redshifts with Gaussian mixture models
av: Hatfield, PW, et al.
Publicerad: (2020) -
Photometric redshift estimation using Gaussian processes
av: Bonfield, D, et al.
Publicerad: (2010)