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Eine Ebene höherGruppiert nach: Dokumententyp |
Veröffentlichungsdatum
Anzahl der Publikationen: 8
2019
Hoyle, Ben und Rau, Markus Michael
(2019):
Self-consistent redshift estimation using correlation functions without a spectroscopic reference sample.
In: Monthly Notices of the Royal Astronomical Society, Bd. 485, Nr. 3: S. 3642-3660
Monsch, Kristina; Ercolano, Barbara; Picogna, Giovanni; Preibisch, Thomas und Rau, Markus Michael
(2019):
The imprint of X-ray photoevaporation of planet-forming discs on the orbital distribution of giant planets.
In: Monthly Notices of the Royal Astronomical Society, Bd. 483, Nr. 3: S. 3448-3458
2017
Rau, Markus Michael; Hoyle, Ben; Päch, Kerstin und Seitz, Stella
(2017):
Correcting cosmological parameter biases for all redshift surveys induced by estimating and reweighting redshift distributions.
In: Monthly Notices of the Royal Astronomical Society, Bd. 466, Nr. 3: S. 2927-2938
2016
Zitlau, Roman; Hoyle, Ben; Paech, Kerstin; Weller, Jochen 
ORCID: https://orcid.org/0000-0002-8282-2010; Rau, Markus Michael und Seitz, Stella
(2016):
Stacking for machine learning redshifts applied to SDSS galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 460, Nr. 3: S. 3152-3162
ORCID: https://orcid.org/0000-0002-8282-2010; Rau, Markus Michael und Seitz, Stella
(2016):
Stacking for machine learning redshifts applied to SDSS galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 460, Nr. 3: S. 3152-3162
Hoyle, Ben; Paech, Kerstin; Rau, Markus Michael; Seitz, Stella und Weller, Jochen ORCID: https://orcid.org/0000-0002-8282-2010
(2016):
Tuning target selection algorithms to improve galaxy redshift estimates.
In: Monthly Notices of the Royal Astronomical Society, Bd. 458, Nr. 4: S. 4498-4511
ORCID: https://orcid.org/0000-0002-8282-2010
(2016):
Tuning target selection algorithms to improve galaxy redshift estimates.
In: Monthly Notices of the Royal Astronomical Society, Bd. 458, Nr. 4: S. 4498-4511
2015
Hoyle, Ben; Rau, Markus Michael; Paech, Kerstin; Bonnett, Christopher; Seitz, Stella und Weller, Jochen ORCID: https://orcid.org/0000-0002-8282-2010
(2015):
Anomaly detection for machine learning redshifts applied to SDSS galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 452, Nr. 4: S. 4183-4194
ORCID: https://orcid.org/0000-0002-8282-2010
(2015):
Anomaly detection for machine learning redshifts applied to SDSS galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 452, Nr. 4: S. 4183-4194
Hoyle, Ben; Rau, Markus Michael; Bonnett, Christopher; Seitz, Stella und Weller, Jochen ORCID: https://orcid.org/0000-0002-8282-2010
(2015):
Data augmentation for machine learning redshifts applied to Sloan Digital Sky Survey galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 450, Nr. 1: S. 305-316
ORCID: https://orcid.org/0000-0002-8282-2010
(2015):
Data augmentation for machine learning redshifts applied to Sloan Digital Sky Survey galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 450, Nr. 1: S. 305-316
Hoyle, Ben; Rau, Markus Michael; Zitlau, Roman; Seitz, Stella und Weller, Jochen ORCID: https://orcid.org/0000-0002-8282-2010
(2015):
Feature importance for machine learning redshifts applied to SDSS galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 449, Nr. 2: S. 1275-1283
ORCID: https://orcid.org/0000-0002-8282-2010
(2015):
Feature importance for machine learning redshifts applied to SDSS galaxies.
In: Monthly Notices of the Royal Astronomical Society, Bd. 449, Nr. 2: S. 1275-1283