Using neural networks to estimate redshift distributions. An application to CFHTLenS

SkyNet: an efficient and robust neural network training tool for machine learning in astronomy

(2014) Philip Graff et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Spectroscopic failures in photometric redshift calibration: cosmological biases and survey requirements

(2014) Carlos E. Cunha et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

The VIMOS Public Extragalactic Survey (VIPERS)

(2013) B. Garilli et al.   ASTRONOMY & ASTROPHYSICS

CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey – imaging data and catalogue products

(2013) T. Erben et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

On using angular cross-correlations to determine source redshift distributions

(2013) M. McQuinn et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests

(2013) Matias Carrasco Kind et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Photometric redshifts with the quasi Newton algorithm (MLPQNA) Results in the PHAT1 contest

(2012) S. Cavuoti et al.   ASTRONOMY & ASTROPHYSICS

Sample variance in photometric redshift calibration: cosmological biases and survey requirements

(2012) Carlos E. Cunha et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Bayesian inference from photometric redshift surveys

(2012) Jens Jasche et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey

(2012) Catherine Heymans et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

CFHTLenS: improving the quality of photometric redshifts with precision photometry★

(2012) H. Hildebrandt et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

EFFECT OF INCLINATION OF GALAXIES ON PHOTOMETRIC REDSHIFT

(2011) Ching-Wa Yip et al.   ASTROPHYSICAL JOURNAL

Unsupervised self-organized mapping: a versatile empirical tool for object selection, classification and redshift estimation in large surveys

(2011) James E. Geach   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

PHAT: PHoto-zAccuracy Testing

(2010) H. Hildebrandt et al.   ASTRONOMY & ASTROPHYSICS

RANDOM FORESTS FOR PHOTOMETRIC REDSHIFTS

(2010) Samuel Carliles et al.   ASTROPHYSICAL JOURNAL

ArborZ: PHOTOMETRIC REDSHIFTS USING BOOSTED DECISION TREES

(2010) David W. Gerdes et al.   ASTROPHYSICAL JOURNAL

Photometric redshifts: estimating their contamination and distribution using clustering information

(2010) Jonathan Benjamin et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Dark-energy constraints and correlations with systematics from CFHTLS weak lensing, SNLS supernovae Ia and WMAP5

(2009) M. Kilbinger et al.   ASTRONOMY & ASTROPHYSICS

NEW APPROACHES TO PHOTOMETRIC REDSHIFT PREDICTION VIA GAUSSIAN PROCESS REGRESSION IN THE SLOAN DIGITAL SKY SURVEY

(2009) M. J. Way et al.   ASTROPHYSICAL JOURNAL

Photometric redshift estimation using spectral connectivity analysis

(2009) P. E. Freeman et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

Bayesian photometric redshifts with empirical training sets

(2009) Christian Wolf   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

The Vimos VLT deep survey

(2008) B. Garilli et al.   ASTRONOMY & ASTROPHYSICS

Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross‐Correlations

(2008) Jeffrey A. Newman   ASTROPHYSICAL JOURNAL