Probabilistic photometric redshift estimation in massive digital sky surveys via machine learning
Abstract: The problem of photometric redshift estimation is a major subject in astronomy, since the need of estimating distances for a huge number of sources, as required by the data deluge of the recent years. The ability to estimate redshifts through spectroscopy does not scale with this avalanche...
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| Main Author: | |
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| Format: | Book/Monograph Thesis |
| Language: | English |
| Published: |
Heidelberg
2019
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| DOI: | 10.11588/heidok.00026000 |
| Subjects: | |
| Online Access: | Resolving-System, kostenfrei, Volltext: http://dx.doi.org/10.11588/heidok.00026000 Resolving-System, kostenfrei, Volltext: http://nbn-resolving.de/urn:nbn:de:bsz:16-heidok-260000 Resolving-System, Volltext: https://nbn-resolving.org/urn:nbn:de:bsz:16-heidok-260000 Langzeitarchivierung Nationalbibliothek, Volltext: http://d-nb.info/1179232658/34 Verlag, kostenfrei, Volltext: http://www.ub.uni-heidelberg.de/archiv/26000 Resolving-System, Unbekannt: https://doi.org/10.11588/heidok.00026000 
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| Author Notes: | Put forward by Antonio D'Isanto ; referees: Prof. Dr. Joachim Wambsganß, Dr. Coryn Bailer-Jones |
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Probabilistic photometric redshift estimation in massive digital sky surveys via machine learning
[2019?]
Book/Monograph
Thesis