The many flavours of photometric redshifts

Random Forests

Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538

Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds

Schlegel, D. J., Finkbeiner, D. P., & Davis, M. (1998) · The Astrophysical Journal · doi:10.1086/305772 · Cited by 15,126

Stellar population synthesis at the resolution of 2003

Bruzual, G. A., & Charlot, S. (2003) · Monthly Notices of the Royal Astronomical Society · doi:10.1046/j.1365-8711.2003.06897.x · Cited by 10,505

SExtractor: Software for source extraction

Bertin, É., & Arnouts, S. (1996) · Astronomy & Astrophysics Supplement Series · doi:10.1051/aas:1996164 · Cited by 8,949

The Dust Content and Opacity of Actively Star‐forming Galaxies

Calzetti, D., Armus, L., Bohlin, R. C., Kinney, A. L., Koornneef, J., & Storchi‐Bergmann, T. (2000) · The Astrophysical Journal · doi:10.1086/308692 · Cited by 5,707

LSST: From Science Drivers to Reference Design and Anticipated Data Products

Ivezić, Ž., Kahn, S. M., Tyson, J. A., Abel, B., Acosta, E., Allsman, R., Alonso, D., AlSayyad, Y., Anderson, S. F., Andrew, J., et al. (2019) · The Astrophysical Journal · doi:10.3847/1538-4357/ab042c · Cited by 4,357

The Demography of Massive Dark Objects in Galaxy Centers

Magorrian, J., Tremaine, S. D., Richstone, D. O., Bender, R., Bower, G., Dressler, A. M., Faber, S. M., Gebhardt, K., Green, R. F., Grillmair, C. J., et al. (1998) · The Astronomical Journal · doi:10.1086/300353 · Cited by 3,986

Evolutionary population synthesis: models, analysis of the ingredients and application to high-z galaxies

Maraston, C. (2005) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2005.09270.x · Cited by 1,907

EAZY: A Fast, Public Photometric Redshift Code

Brammer, G. B., van Dokkum, P. G., & Coppi, P. (2008) · The Astrophysical Journal · doi:10.1086/591786 · Cited by 1,876

Physics of the Interstellar and Intergalactic Medium

Draine, B. T. (2011) · doi:10.1515/9781400839087 · Cited by 1,787

Accurate photometric redshifts for the CFHT legacy survey calibrated using the VIMOS VLT deep survey

Ilbert, O., Arnouts, S., McCracken, H. J., Bolzonella, M., Bertin, E., Fèvre, O. C. L., Mellier, Y., Zamorani, G., Pelló, R., Iovino, A., et al. (2006) · Astronomy and Astrophysics · doi:10.1051/0004-6361:20065138 · Cited by 1,683

UV LUMINOSITY FUNCTIONS AT REDSHIFTS z ∼ 4 TO z ∼ 10: 10,000 GALAXIES FROM HST LEGACY FIELDS

Bouwens, R. J., Illingworth, G. D., Oesch, P. A., Trenti, M., Labbé, I., Bradley, L., Carollo, C. M., van Dokkum, P. G., Gonzalez, V., Holwerda, B. W., et al. (2015) · The Astrophysical Journal · doi:10.1088/0004-637x/803/1/34 · Cited by 1,298

COSMOS PHOTOMETRIC REDSHIFTS WITH 30-BANDS FOR 2-deg 2

Ilbert, O., Capak, P. L., Salvato, M., Aussel, H., McCracken, H. J., Sanders, D. B., Scoville, N., Kartaltepe, J. S., Arnouts, S., Floc'h, E. L., et al. (2008) · The Astrophysical Journal · doi:10.1088/0004-637x/690/2/1236 · Cited by 1,258

Colors and magnitudes predicted for high redshift galaxies

Coleman, G. D., Wu, C., & Weedman, D. W. (1980) · The Astrophysical Journal Supplement Series · doi:10.1086/190674 · Cited by 1,223

Radiative transfer in a clumpy universe: The colors of high-redshift galaxies

Madau, P. (1995) · The Astrophysical Journal · doi:10.1086/175332 · Cited by 1,183

THE COSMOS2015 CATALOG: EXPLORING THE 1 < z < 6 UNIVERSE WITH HALF A MILLION GALAXIES

Laigle, C., McCracken, H. J., Ilbert, O., Hsieh, B.-C., Davidzon, I., Capak, P. L., Hasinger, G., Silverman, J. D., Pichon, C., Coupon, J., et al. (2016) · The Astrophysical Journal Supplement Series · doi:10.3847/0067-0049/224/2/24 · Cited by 1,145

Cosmology and fundamental physics with the Euclid satellite

The Euclid Theory Working Group, Amendola, L., Appleby, S. A., Avgoustidis, A., Bacon, D., Baker, T., Baldi, M., Bartolo, N., Blanchard, A., Bonvin, C., et al. (2018) · Living Reviews in Relativity · doi:10.1007/s41114-017-0010-3 · Cited by 1,096

The Dark Energy Survey: more than dark energy – an overview

Dark Energy Survey Collaboration, Abbott, T. M. C., Abdalla, F. B., Aleksić, J., Allam, S., Amara, A., Bacon, D., Balbinot, E., Banerji, M., Bechtol, K., et al. (2016) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stw641 · Cited by 1,073

Measuring and modelling the redshift evolution of clustering: the Hubble Deep Field North

Arnouts, S., Cristiani, S., Moscardini, L., Matarrese, S., Lucchin, F., Fontana, A., & Giallongo, E. (1999) · Monthly Notices of the Royal Astronomical Society · doi:10.1046/j.1365-8711.1999.02978.x · Cited by 982

Bayesian Photometric Redshift Estimation

Benı́tez, N. (1998) · The Astrophysical Journal · doi:10.1086/308947 · Cited by 974

Template Ultraviolet to Near-Infrared Spectra of Star-forming Galaxies and Their Application to K-Corrections

Kinney, A. L., Calzetti, D., Bohlin, R. C., McQuade, K., Storchi‐Bergmann, T., & Schmitt, H. R. (1996) · The Astrophysical Journal · doi:10.1086/177583 · Cited by 926

Cosmology and Fundamental Physics with the Euclid Satellite

The Euclid Theory Working Group, Amendola, L., Appleby, S., Bacon, D., Baker, T., Baldi, M., Bartolo, N., Blanchard, A., Bonvin, C., Borgani, S., et al. (2013) · Living Reviews in Relativity · doi:10.12942/lrr-2013-6 · Cited by 899

Spectral Energy Distributions of Hard X‐Ray Selected Active Galactic Nuclei in the XMM‐Newton Medium Deep Survey

Polletta, M. D. C., Tajer, M., Maraschi, L., Trinchieri, G., Lonsdale, C. J., Chiappetti, L., Andreon, S., Pierre, M., Fèvre, O. C. L., Zamorani, G., et al. (2007) · The Astrophysical Journal · doi:10.1086/518113 · Cited by 868

The Hyper Suprime-Cam SSP Survey: Overview and survey design

Aihara, H., Arimoto, N., Armstrong, R., Arnouts, S., Bahcall, N. A., Bickerton, S. J., Bosch, J., Bundy, K. A., Capak, P. L., Chan, J. H. H., et al. (2018) · RECERCAT (Consorci de Serveis Universitaris de Catalunya) · Cited by 749

COSMOS Photometric Redshifts with 30-bands for 2-deg2Preprint

Ilbert, O., Capak, P., Salvato, M., et al. (2008) · HAL (Le Centre pour la Communication Scientifique Directe) · doi:10.48550/arxiv.0809.2101 · Cited by 708

ANNz: Estimating Photometric Redshifts Using Artificial Neural Networks

Collister, A. A., & Lahav, O. (2004) · Publications of the Astronomical Society of the Pacific · doi:10.1086/383254 · Cited by 498

THE NEWFIRM MEDIUM-BAND SURVEY: PHOTOMETRIC CATALOGS, REDSHIFTS, AND THE BIMODAL COLOR DISTRIBUTION OF GALAXIES OUT TO z ∼ 3

Whitaker, K. E., Labbé, I., van Dokkum, P. G., Brammer, G., Kriek, M., Marchesini, D., Quadri, R. F., Franx, M., Muzzin, A., Williams, R. J., et al. (2011) · The Astrophysical Journal · doi:10.1088/0004-637x/735/2/86 · Cited by 497

EMU: Evolutionary Map of the Universe

Norris, R. P., Hopkins, A. M., Afonso, J., Brown, S., Condon, J. J., Dunne, L., Feain, I., Hollow, R. P., Jarvis, M., Johnston-Hollitt, M., et al. (2011) · Publications of the Astronomical Society of Australia · doi:10.1071/as11021 · Cited by 425

Power Spectrum Tomography with Weak Lensing

Hu, W. (1999) · The Astrophysical Journal · doi:10.1086/312210 · Cited by 420

A catalogue of the Chandra Deep Field South with multi-colour classification and photometric redshifts from COMBO-17

Wolf, C., Meisenheimer, K., Kleinheinrich, M., Borch, A., Dye, S., Gray, M. E., Wisotzki, L., Bell, E. F., Rix, H., Cimatti, A., et al. (2004) · Astronomy and Astrophysics · doi:10.1051/0004-6361:20040525 · Cited by 416

J-PAS: The Javalambre-Physics of the Accelerated Universe Astrophysical SurveyPreprint

Benítez, N., Dupke, R. A., Moles, M., Junior, L. S., Cenarro, J., Marín-Franch, A., Taylor, K., Cristóbal, D., Fernández-Soto, A., de Oliveira, C. M., et al. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1403.5237 · Cited by 398

The VIMOS VLT Deep Survey - First epoch VVDS-Deep survey: 11564 spectra with 17.5<=IAB<=24, and the redshift distribution over 0< z <=5

Fèvre, O. C. L., Vettolani, G., Garilli, B., Tresse, L., Bottini, D., Brun, V. L., Maccagni, D., Picat, J. P., Scaramella, R., Scodeggio, M., et al. (2005) · HAL · doi:10.1051/0004-6361:20041960 · Cited by 393

PHOTOMETRIC REDSHIFT AND CLASSIFICATION FOR THEXMM-COSMOS SOURCES

Salvato, M., Hasinger, G., Ilbert, O., Zamorani, G., Brusa, M., Scoville, N. Z., Rau, A., Capak, P. L., Arnouts, S., Aussel, H., et al. (2008) · The Astrophysical Journal · doi:10.1088/0004-637x/690/2/1250 · Cited by 375

A CRITICAL ASSESSMENT OF PHOTOMETRIC REDSHIFT METHODS: A CANDELS INVESTIGATION

Dahlen, T., Mobasher, B., Faber, S. M., Ferguson, H. C., Barro, G., Finkelstein, S. L., Finlator, K., Fontana, A., Gruetzbauch, R., Johnson, S., et al. (2013) · The Astrophysical Journal · doi:10.1088/0004-637x/775/2/93 · Cited by 364

THE CHANDRA COSMOS LEGACY SURVEY: OPTICAL/IR IDENTIFICATIONS

Marchesi, S., Civano, F., Elvis, M., Salvato, M., Brusa, M., Comastri, A., Gilli, R., Hasinger, G., Lanzuisi, G., Miyaji, T., et al. (2016) · The Astrophysical Journal · doi:10.3847/0004-637x/817/1/34 · Cited by 340

THEXMM-NEWTONWIDE-FIELD SURVEY IN THE COSMOS FIELD (XMM-COSMOS): DEMOGRAPHY AND MULTIWAVELENGTH PROPERTIES OF OBSCURED AND UNOBSCURED LUMINOUS ACTIVE GALACTIC NUCLEI

Brusa, M., Civano, F., Comastri, A., Miyaji, T., Salvato, M., Zamorani, G., Cappelluti, N., Fiore, F., Hasinger, G., Mainieri, V., et al. (2010) · The Astrophysical Journal · doi:10.1088/0004-637x/716/1/348 · Cited by 334

Frank Rosenblatt: Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms

Malsburg, C. V. D. (1986) · Springer eBooks · doi:10.1007/978-3-642-70911-1_20 · Cited by 305

The XMM‐Newton Wide‐Field Survey in the COSMOS Field: Statistical Properties of Clusters of Galaxies

Finoguenov, A., Guzzo, L., Hasinger, G., Scoville, N. Z., Aussel, H., Böhringer, H., Brusa, M., Capak, P. L., Cappelluti, N., Comastri, A., et al. (2007) · The Astrophysical Journal Supplement Series · doi:10.1086/516577 · Cited by 301

The K20 survey

Cimatti, A., Daddi, E., Mignoli, M., Pozzetti, L., Renzini, A., Zamorani, G., Broadhurst, T. J., Fontana, A., Saracco, P., Poli, F., et al. (2002) · Astronomy and Astrophysics · doi:10.1051/0004-6361:20011696 · Cited by 289

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

Kind, M. C., & Brunner, R. J. (2013) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stt574 · Cited by 288

THE SPECTRAL ENERGY DISTRIBUTIONS OF z ∼ 8 GALAXIES FROM THE IRAC ULTRA DEEP FIELDS: EMISSION LINES, STELLAR MASSES, AND SPECIFIC STAR FORMATION RATES AT 650 MYR

Labbé, I., Oesch, P. A., Bouwens, R. J., Illingworth, G. D., Magee, D. K., González, V., Carollo, C. M., Franx, M., Trenti, M., van Dokkum, P., et al. (2013) · The Astrophysical Journal Letters · doi:10.1088/2041-8205/777/2/l19 · Cited by 288

Calibrating Redshift Distributions beyond Spectroscopic Limits with Cross‐Correlations

Newman, J. A. (2008) · The Astrophysical Journal · doi:10.1086/589982 · Cited by 285

Dark energy survey year 1 results: photometric data set for cosmology

Lima, M. V. B. T. (2017) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · doi:10.3847/1538-4365/aab4f5/meta · Cited by 278

ANNz: estimating photometric redshifts using artificial neural networksPreprint

Collister, A., & Lahav, O. (2003) · doi:10.48550/arxiv.astro-ph/0311058 · Cited by 275

THE MULTIWAVELENGTH SURVEY BY YALE–CHILE (MUSYC): DEEP MEDIUM-BAND OPTICAL IMAGING AND HIGH-QUALITY 32-BAND PHOTOMETRIC REDSHIFTS IN THE ECDF-S

Cardamone, C. N., van Dokkum, P. G., Urry, C. M., Taniguchi, Y., Gawiser, E., Brammer, G., Taylor, E., Damen, M., Treister, E., Cobb, B. E., et al. (2010) · The Astrophysical Journal Supplement Series · doi:10.1088/0067-0049/189/2/270 · Cited by 273

PHAT: PHoto-zAccuracy Testing

Hildebrandt, H., Arnouts, S., Capak, P. L., Moustakas, L. A., Wolf, C., Abdalla, F. B., Assef, R. J., Banerji, M., Benítez, N., Brammer, G. B., et al. (2010) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201014885 · Cited by 270

The Zurich Extragalactic Bayesian Redshift Analyzer and its first application: COSMOS

Feldmann, R., Carollo, C. M., Porciani, C., Lilly, S. J., Capak, P. L., Taniguchi, Y., Fèvre, O. C. L., Renzini, A., Scoville, N. Z., Ajiki, M., et al. (2006) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2006.10930.x · Cited by 268

DISSECTING PHOTOMETRIC REDSHIFT FOR ACTIVE GALACTIC NUCLEUS USINGXMM- ANDCHANDRA-COSMOS SAMPLES

Salvato, M., Ilbert, O., Hasinger, G., Rau, A., Civano, F., Zamorani, G., Brusa, M., Elvis, M., Vignali, C., Aussel, H., et al. (2011) · The Astrophysical Journal · doi:10.1088/0004-637x/742/2/61 · Cited by 268

Estimating the redshift distribution of photometric galaxy samples – II. Applications and tests of a new method

Lima, M., Cunha, C., Oyaizu, H., Frieman, J., Lin, H., & Sheldon, E. (2008) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2008.13510.x · Cited by 256

CFHTLenS: Improving the quality of photometric redshifts with precision photometry

Hildebrandt, H., Erben, T., Kuijken, K., van Waerbeke, L., Heymans, C., Coupon, J., Benjamin, J., Bonnett, C., Fu, L., Hoekstra, H., et al. (2011) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2012.20468.x · Cited by 254

Accreting supermassive black holes in the COSMOS field and the connection to their host galaxies

Bongiorno, A., Merloni, A., Brusa, M., Magnelli, B., Salvato, M., Mignoli, M., Zamorani, G., Fiore, F., Rosario, D. J., Mainieri, V., et al. (2012) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2012.22089.x · Cited by 253

Star-forming galaxies at very high redshifts

Lanzetta, K. M., Yahil, A., & Fernández-Soto, A. (1996) · Nature · doi:10.1038/381759a0 · Cited by 212

ANNz2: Photometric Redshift and Probability Distribution Function Estimation using Machine Learning

Sadeh, I., Abdalla, F. B., & Lahav, O. (2016) · Publications of the Astronomical Society of the Pacific · doi:10.1088/1538-3873/128/968/104502 · Cited by 202

On the physical properties ofz≈6–8 galaxies

Schaerer, D., & de Barros, S. (2010) · Astronomy and Astrophysics · doi:10.1051/0004-6361/200913946 · Cited by 198

A Critical Assessment Of Photometric Redshift Methods: A CANDELS Investigation

Wilson, G. (2016) · Texas ScholarWorks (Texas Digital Library) · doi:10.15781/t2kz5w · Cited by 194

The WIRCam Deep Survey

Bielby, R. M., Hudelot, P., McCracken, H. J., Ilbert, O., Daddi, E., Fèvre, O. C. L., González-Pérez, V., Kneib, J., Marmo, C., Mellier, Y., et al. (2012) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201118547 · Cited by 189

Photometric redshifts for the CFHTLS T0004 deep and wide fields

Coupon, J., Ilbert, O., Kilbinger, M., McCracken, H. J., Mellier, Y., Arnouts, S., Bertin, E., Hudelot, P., Schultheis, M., Fèvre, O. C. L., et al. (2009) · Astronomy and Astrophysics · doi:10.1051/0004-6361/200811413 · Cited by 188

Photometric redshifts for the SDSS Data Release 12

Beck, R. E., Dobos, L., Budavári, T., Szalay, A. S., & Csabai, I. (2016) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stw1009 · Cited by 188

TFIT: A Photometry Package Using Prior Information for Mixed‐Resolution Data Sets

Laidler, V. G., Papovich, C., Grogin, N. A., Idzi, R., Dickinson, M., Ferguson, H. C., Hilbert, B., Clubb, K. I., & Ravindranath, S. (2007) · Publications of the Astronomical Society of the Pacific · doi:10.1086/523898 · Cited by 185

Photometric redshift estimation via deep learning

D’Isanto, A., & Polsterer, K. L. (2017) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201731326 · Cited by 180

Photometric redshift analysis in the Dark Energy Survey Science Verification data

Sánchez, C., Kind, M. C., Lin, H., Miquel, R., Abdalla, F. B., Amara, A., Banerji, M., Bonnett, C., Brunner, R. J., Capozzi, D., et al. (2014) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stu1836 · Cited by 178

RANDOM FORESTS FOR PHOTOMETRIC REDSHIFTS

Carliles, S., Budavári, T., Heinis, S., Priebe, C. E., & Szalay, A. S. (2010) · The Astrophysical Journal · doi:10.1088/0004-637x/712/1/511 · Cited by 171

Photometric Redshifts and Selection of High-Redshift Galaxies in the NTT and Hubble Deep Fields

Fontana, A., D’Odorico, S., Poli, F., Giallongo, E., Arnouts, S., Cristiani, S., Moorwood, A. F. M., & Saracco, P. (2000) · The Astronomical Journal · doi:10.1086/316803 · Cited by 165

A critical analysis of the ultraviolet continuum slopes (β) of high-redshift galaxies: no evidence (yet) for extreme stellar populations at z > 6

Dunlop, J. S., McLure, R. J., Robertson, B. E., Ellis, R. S., Stark, D. P., Cirasuolo, M., & de Ravel, L. (2011) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2011.20102.x · Cited by 160

The galaxy–halo connection from a joint lensing, clustering and abundance analysis in the CFHTLenS/VIPERS field

Coupon, J., Arnouts, S., Waerbeke, L. V., Moutard, T., Ilbert, O., van Uitert, E., Erben, T., Garilli, B., Guzzo, L., Heymans, C., et al. (2015) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stv276 · Cited by 159

T-PHOT: A new code for PSF-matched, prior-based, multiwavelength extragalactic deconfusion photometry

Merlin, E., Fontana, A., Ferguson, H. C., Dunlop, J. S., Elbaz, D., Bourne, N., Bruce, V. A., Buitrago, F., Castellano, M., Schreiber, C., et al. (2015) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201526471 · Cited by 159

PHOTOMETRIC REDSHIFT WITH BAYESIAN PRIORS ON PHYSICAL PROPERTIES OF GALAXIES

Tanaka, M. (2015) · The Astrophysical Journal · doi:10.1088/0004-637x/801/1/20 · Cited by 154

IDENTIFICATIONS AND PHOTOMETRIC REDSHIFTS OF THE 2 Ms CHANDRA DEEP FIELD-SOUTH SOURCES

Luo, B., Brandt, W. N., Xue, Y. Q., Brusa, M., Alexander, D. M., Bauer, F. E., Comastri, A., Koekemoer, A. M., Lehmer, B. D., Mainieri, V., et al. (2010) · The Astrophysical Journal Supplement Series · doi:10.1088/0067-0049/187/2/560 · Cited by 153

The dominant role of mergers in the size evolution of massive early-type galaxies since z ~ 1

López-Sanjuán, C., Fèvre, O. C. L., Ilbert, O., Tasca, L. A. M., Bridge, C., Cucciati, O., Kampczyk, P., Pozzetti, L., Xu, C. K., Carollo, C. M., et al. (2012) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201219085 · Cited by 151

CANDELS/GOODS-S, CDFS, AND ECDFS: PHOTOMETRIC REDSHIFTS FOR NORMAL AND X-RAY-DETECTED GALAXIES

Hsu, L.-T., Salvato, M., Nandra, K., Brusa, M., Bender, R., Büchner, J., Donley, J. L., Kocevski, D. D., Guo, Y., Hathi, N. P., et al. (2014) · The Astrophysical Journal · doi:10.1088/0004-637x/796/1/60 · Cited by 150

Measuring photometric redshifts using galaxy images and Deep Neural Networks

Hoyle, B. (2016) · Astronomy and Computing · doi:10.1016/j.ascom.2016.03.006 · Cited by 144

SHARDS: AN OPTICAL SPECTRO-PHOTOMETRIC SURVEY OF DISTANT GALAXIES

Pérez‐González, P. G., Cava, A., Barro, G., Villar, V., Cardiel, N., Ferreras, I., Rodríguez-Espinosa, J. M., Alonso‐Herrero, A., Balcells, M., Cenarro, A. J., et al. (2012) · The Astrophysical Journal · doi:10.1088/0004-637x/762/1/46 · Cited by 136

PHOTOMETRIC REDSHIFTS AND QUASAR PROBABILITIES FROM A SINGLE, DATA-DRIVEN GENERATIVE MODEL

Bovy, J., Myers, A. D., Hennawi, J. F., Hogg, D. W., McMahon, R. G., Schiminovich, D., Sheldon, E. S., Brinkmann, J., Schneider, D. P., & Weaver, B. A. (2012) · The Astrophysical Journal · doi:10.1088/0004-637x/749/1/41 · Cited by 133

Relative merits of different types of rest-frame optical observations to constrain galaxy physical parameters

Pacifici, C., Charlot, S., Blaizot, J., & Brinchmann, J. (2012) · Monthly Notices of the Royal Astronomical Society · doi:10.1111/j.1365-2966.2012.20431.x · Cited by 132

The third data release of the Kilo-Degree Survey and associated data products

de Jong, J. D., Kleijn, G. V. V., Erben, T., Hildebrandt, H., Kuijken, K., Sikkema, G., Brescia, M., Bilicki, M., Napolitano, N., Amaro, V., et al. (2017) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201730747 · Cited by 132

RESOLVING THE DISCREPANCY OF GALAXY MERGER FRACTION MEASUREMENTS AT z ∼ 0–3

Man, A. W. S., Zirm, A., & Toft, S. (2016) · The Astrophysical Journal · doi:10.3847/0004-637x/830/2/89 · Cited by 128

Photometric redshifts with the Multilayer Perceptron Neural Network: Application to the HDF-S and SDSS

Vanzella, E., Cristiani, S., Fontana, A., Nonino, M., Arnouts, S., Giallongo, E., Grazian, A., Fasano, G., Popesso, P., Saracco, P., et al. (2004) · Astronomy and Astrophysics · doi:10.1051/0004-6361:20040176 · Cited by 127

SOMz: photometric redshift PDFs with self-organizing maps and random atlas

Kind, M. C., & Brunner, R. J. (2014) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stt2456 · Cited by 119

Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

Bonnett, C., Troxel, M., Hartley, W., Amara, A., Leistedt, B., Becker, M., Bernstein, G., Bridle, S., Bruderer, C., Busha, M., et al. (2015) · Physical Review D · doi:10.1103/physrevd.94.042005 · Cited by 113

MAPPING THE GALAXY COLOR–REDSHIFT RELATION: OPTIMAL PHOTOMETRIC REDSHIFT CALIBRATION STRATEGIES FOR COSMOLOGY SURVEYS

Masters, D., Capak, P., Stern, D., Ilbert, O., Salvato, M., Schmidt, S., Longo, G., Rhodes, J., Paltani, S., Mobasher, B., et al. (2015) · The Astrophysical Journal · doi:10.1088/0004-637x/813/1/53 · Cited by 113

Photometric Redshift of X‐Ray Sources in the Chandra Deep Field–South

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The ALHAMBRA Survey: Bayesian photometric redshifts with 23 bands for 3 deg2

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