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Improving machine learning-derived photometric redshifts an..:
Humphrey, A
;
Cunha, P A C
;
Paulino-Afonso, A
...
Monthly Notices of the Royal Astronomical Society. 520 (2022) 1 - p. 305-313 , 2022
Link:
https://doi.org/10.1093/mnras/stac3596
RT Journal T1 <Title>Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1093_mnras_stac3596&Exemplar=1&LAN=DE A1 Humphrey, A A1 Cunha, P A C A1 Paulino-Afonso, A A1 Amarantidis, S A1 Carvajal, R A1 Gomes, J M A1 Matute, I A1 Papaderos, P PB Oxford University Press (OUP) YR 2022 SN 0035-8711 SN 1365-2966 JF Monthly Notices of the Royal Astronomical Society VO 520 IS 1 SP 305 OP 313 LK http://dx.doi.org/https://doi.org/10.1093/mnras/stac3596 DO https://doi.org/10.1093/mnras/stac3596 SF ELIB - SuUB Bremen
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