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