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...
Main Authors: | Almosallam, I, Jarvis, M, Roberts, S |
---|---|
Format: | Journal article |
Published: |
Oxford University Press
2016
|
Similar Items
-
GPz: Non-stationary sparse Gaussian processes for heteroscedastic uncertainty estimation in photometric redshifts
by: Almosallam, I, et al.
Published: (2016) -
A Sparse Gaussian Process Framework for Photometric Redshift Estimation
by: Almosallam, I, et al.
Published: (2015) -
Improving Photometric Redshift Estimation using GPz: size information,
post processing and improved photometry
by: Gomes, Z, et al.
Published: (2017) -
Photometric redshift estimation using Gaussian processes
by: Bonfield, D, et al.
Published: (2010) -
Heteroscedastic Gaussian processes for uncertain and incomplete data
by: Almosallam, I
Published: (2017)