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