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Journal of Geodesy, ISSN 0949-7714, 9/2018, Volume 92, Issue 9, pp. 1003 - 1021
In this paper, we consistently estimate geodetic parameters such as weekly 3-D station coordinates, Earth orientation parameters (EOP) including daily x/y-pole... 
Earth Sciences | Stokes coefficients | Starlette | GGOS | LARES | EOP | TRF | Ajisai | Stella | Geophysics/Geodesy | Earth Sciences, general | LAGEOS | Etalon | SLR | BLITS | Larets | Multi-satellite | SYSTEM | MISSION | GRAVITY-FIELD | GEOCHEMISTRY & GEOPHYSICS | REMOTE SENSING | MODELS | REFERENCE FRAME | Artificial satellites | Gravity | Gravity field | Correlation | Parameters | Terrestrial environments | Satellite sensing | Coefficients | Orientation | Remote sensing | Earth | Satellites | Solutions | Lasers | Weekly | Translations
Journal Article
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 04/2017, Volume 466, Issue 3, p. 2927
  Photometric redshift uncertainties are a major source of systematic error for ongoing and future photometric surveys. We study different sources of redshift... 
Tomography | Cosmology | Calibration | Dark energy | Star & galaxy formation
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 04/2017, Volume 466, Issue 3, pp. 2927 - 2927
Photometric redshift uncertainties are a major source of systematic error for ongoing and future photometric surveys. We study different sources of redshift... 
Permissible error | Histograms | Spectroscopy | Red shift | Parameters | Systematic errors | Calibration | Photometry
Journal Article
Journal Article
Astrophysical Journal, ISSN 0004-637X, 01/2013, Volume 762, Issue 1
We present a candidate for the most distant galaxy known to date with a photometric redshift z = 10.7 +0.6 / -0.4 (95% confidence limits; with z < 9.5 galaxies... 
early universe | galaxies: evolution | galaxies: distances and redshifts | galaxies: high-redshift | gravitational lensing: strong | Physics - Cosmology and Nongalactic Astrophysics
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 12/2012, Volume 427, Issue 3, pp. 1918 - 1939
Journal Article
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 03/2016, Volume 458, Issue 4, pp. 4498 - 4511
We showcase machine learning (ML) inspired target selection algorithms to determine which of all potential targets should be selected first for spectroscopic... 
Surveys | Catalogues | Galaxies: Distances and redshifts
Journal Article
Astrophysical Journal, Supplement Series, ISSN 0067-0049, 04/2012, Volume 199, Issue 2, pp. 25 - 23
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 2017, Volume 466, Issue 3, pp. 2927 - 2938
Photometric redshift uncertainties are a major source of systematic error for ongoing and future photometric surveys. We study different sources of redshift... 
Surveys | Galaxies: distances and redshifts | catalogues | CALIBRATION | ERRORS | galaxies: distances and redshifts | ASTRONOMY & ASTROPHYSICS | surveys | MACHINE | COSMIC SHEAR | CFHTLENS | Physics - Cosmology and Nongalactic Astrophysics
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 08/2016, Volume 460, Issue 3, p. 3152
  We present an analysis of a general machine learning technique called 'stacking' for the estimation of photometric redshifts. Stacking techniques can feed... 
Red shift | Algorithms | Stars & galaxies | Artificial intelligence | Astronomy
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 08/2016, Volume 460, Issue 3, pp. 3152 - 3152
We present an analysis of a general machine learning technique called 'stacking' for the estimation of photometric redshifts. Stacking techniques can feed the... 
Learning | Red shift | Algorithms | Stacking | Machine learning | Computational efficiency | Decision trees | Photometry
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 06/2016, Volume 458, Issue 4, pp. 4498 - 4498
We showcase machine learning (ML) inspired target selection algorithms to determine which of all potential targets should be selected first for spectroscopic... 
Spectroscopy | Construction | Red shift | Algorithms | Galaxies | Bias | Sky surveys (astronomy) | Estimates
Journal Article
Monthly Notices of the Royal Astronomical Society, ISSN 0035-8711, 06/2016, Volume 458, Issue 4, p. 4498
  We showcase machine learning (ML) inspired target selection algorithms to determine which of all potential targets should be selected first for spectroscopic... 
Algorithms | Comparative analysis | Artificial intelligence | Star & galaxy formation
Journal Article