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Approximate Bayesian Computation (ABC) is a method to obtain a posterior distribution without a likelihood function, using simulations and a set of distance metrics.
Regression quantiles
Roger Koenker and Gilbert Bassett · 1978
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SExtractor: Software for source extraction
E. Bertin and S. Arnouts · 1996
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Pressure Matching for Hydrocarbon Reservoirs: A Case Study in the Use of Bayes Linear Strategies for Large Computer Experiments
Peter S. Craig, Michael Goldstein, Allan H. Seheult, and James A. Smith · 1997
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An Introduction to Support Vector Machines: And Other Kernel-based Learning Methods
Nello Cristianini and John Shawe-Taylor · 2000
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Markov chain Monte Carlo without likelihoods
P. Marjoram, J. Molitor, V. Plagnol, and S. Tavaré · 2003
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Quantile regression: applications and current research areas
Keming Yu, Zudi Lu, and Julian Stander · 2003
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Warped gaussian processes
Edward Snelson, Carl Edward, and Rasmussen Zoubin Ghahramani · 2004
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Heteroscedastic gaussian process regression
Quoc V. Le, Alex J. Smola, and Stéphane Canu · 2005
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A Simple Quantile Regression via Support Vector Machine
Changha Hwang and Jooyong Shim · 2005
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Nonparametric quantile estimation
Ichiro Takeuchi, Quoc V. Le, Timothy D. Sears, Alexander J. Smola, and Chris Williams · 2006
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Sequential Monte Carlo without likelihoods
S. A. Sisson, Y. Fan, and M. M. Tanaka · 2007
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The First Release COSMOS Optical and Near-IR Data and Catalog
P. Capak, H. Aussel, M. Ajiki, H. J. McCracken, B. Mobasher, N. Scoville, P. Shopbell, Y. Taniguchi, D. Thompson, S. Tribiano, S. Sasaki, A. W. Blain, M. Brusa, C. Carilli, A. Comastri, C. M. Carollo, P. Cassata, J. Colbert, R. S. Ellis, M. Elvis, M. Giavalisco, W. Green, L. Guzzo, G. Hasinger, O. Ilbert, C. Impey, K. Jahnke, J. Kartaltepe, J.-P. Kneib, J. Koda, A. Koekemoer, Y. Komiyama, A. Leauthaud, O. Le Fevre, S. Lilly, C. Liu, R. Massey, S. Miyazaki, T. Murayama, T. Nagao, J. A. Peacock, A. Pickles, C. Porciani, A. Renzini, J. Rhodes, M. Rich, M. Salvato, D. B. Sanders, C. Scarlata, D. Schiminovich, E. Schinnerer, M. Scodeggio, K. Sheth, Y. Shioya, L. A. M. Tasca, J. E. Taylor, L. Yan, and G. Zamorani · 2007
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The Cosmic Evolution Survey (COSMOS): Subaru Observations of the HST Cosmos Field
Y. Taniguchi, N. Scoville, T. Murayama, D. B. Sanders, B. Mobasher, H. Aussel, P. Capak, M. Ajiki, S. Miyazaki, Y. Komiyama, Y. Shioya, T. Nagao, S. S. Sasaki, J. Koda, C. Carilli, M. Giavalisco, L. Guzzo, G. Hasinger, C. Impey, O. LeFevre, S. Lilly, A. Renzini, M. Rich, E. Schinnerer, P. Shopbell, N. Kaifu, H. Karoji, N. Arimoto, S. Okamura, and K. Ohta · 2007
Cited alongside, same era.
Kernel methods in machine learning
Thomas Hofmann, Bernhard Schölkopf, and Alexander J Smola · 2008
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Simulation-based model selection for dynamical systems in systems and population biology
T. Toni and M. P. H. Stumpf · 2009
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Gaussian process regression with student-t likelihood
Jarno Vanhatalo, Pasi Jylänki, and Aki Vehtari · 2009
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Approximate bayesian computation (abc) in practice
Katalin Csillery, Michael G.B. Blum, Oscar E. Gaggiotti, and Olivier Francois · 2010
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An Ultra Fast Image Generator (UFIG) for wide-field astronomy
J. Bergé, L. Gamper, A. Réfrégier, and A. Amara · 2013
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Accelerating ABC methods using Gaussian processes
Richard Wilkinson · 2014
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The Third Gravitational Lensing Accuracy Testing (GREAT3) Challenge Handbook
R. Mandelbaum, B. Rowe, J. Bosch, C. Chang, F. Courbin, M. Gill, M. Jarvis, A. Kannawadi, T. Kacprzak, C. Lackner, A. Leauthaud, H. Miyatake, R. Nakajima, J. Rhodes, M. Simet, J. Zuntz, B. Armstrong, S. Bridle, J. Coupon, J. P. Dietrich, M. Gentile, C. Heymans, A. S. Jurling, S. M. Kent, D. Kirkby, D. Margala, R. Massey, P. Melchior, J. Peterson, A. Roodman, and T. Schrabback · 2014
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Approximate Bayesian computation for forward modeling in cosmology
J. Akeret, A. Refregier, A. Amara, S. Seehars, and C. Hasner · 2015
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The z z < 1.2 Optical Luminosity Function from a Sample of 410,000 Galaxies in Bo#1255tes
R. Beare, M. J. I. Brown, K. Pimbblet, F. Bian, and Y.-T. Lin · 2015
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Estimating conditional quantiles with the help of the pinball loss
Ingo Steinwart and Andreas Christmann · 2011
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Approximate bayesian computational methods
Jean-Michel Marin, Pierre Pudlo, Christian P. Robert, and Robin J. Ryder · 2012
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Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox
J. Vanhatalo, J. Riihimäki, J. Hartikainen, P. Jylänki, V. Tolvanen, and A. Vehtari · 2012
Cited alongside, same era.
CFHTLenS: improving the quality of photometric redshifts with precision photometry
H. Hildebrandt, T. Erben, K. Kuijken, L. van Waerbeke, C. Heymans, J. Coupon, J. Benjamin, C. Bonnett, L. Fu, H. Hoekstra, T. D. Kitching, Y. Mellier, L. Miller, M. Velander, M. J. Hudson, B. T. P. Rowe, T. Schrabback, E. Semboloni, and N. Benítez · 2012
Cited alongside, same era.
Likelihood-free Cosmological Inference with Type Ia Supernovae: Approximate Bayesian Computation for a Complete Treatment of Uncertainty
A. Weyant, C. Schafer, and W. M. Wood-Vasey · 2013
Cited alongside, same era.
Support vector machine quantile regression approach for functional data: Simulation and application studies
Christophe Crambes, Ali Gannoun, and Yousri Henchiri · 2013
Cited alongside, same era.
The VIMOS VLT Deep Survey final data release: a spectroscopic sample of 35 016 galaxies and AGN out to z 6.7 selected with 17.5 ≤ {\leq} i AB
O. Le Fèvre, P. Cassata, O. Cucciati, B. Garilli, O. Ilbert, V. Le Brun, D. Maccagni, C. Moreau, M. Scodeggio, L. Tresse, G. Zamorani, C. Adami, S. Arnouts, S. Bardelli, M. Bolzonella, M. Bondi, A. Bongiorno, D. Bottini, A. Cappi, S. Charlot, P. Ciliegi, T. Contini, S. de la Torre, S. Foucaud, P. Franzetti, I. Gavignaud, L. Guzzo, A. Iovino, B. Lemaux, C. López-Sanjuan, H. J. McCracken, B. Marano, C. Marinoni, A. Mazure, Y. Mellier, R. Merighi, P. Merluzzi, S. Paltani, R. Pellò, A. Pollo, L. Pozzetti, R. Scaramella, L. Tasca, D. Vergani, G. Vettolani, A. Zanichelli, and E. Zucca
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A new approach for obtaining cosmological constraints from Type Ia Supernovae using Approximate Bayesian Computation
E. Jennings, R. Wolf, and M. Sako · 2016
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astroABC : An Approximate Bayesian Computation Sequential Monte Carlo sampler for cosmological parameter estimation
E. Jennings and M. Madigan · 2017
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Lensing substructure quantification in RXJ1131-1231: a 2 keV lower bound on dark matter thermal relic mass
S. Birrer, A. Amara, and A. Refregier · 2017
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Inferring the size and photometric evolution of galaxies from image simulations
S. Carassou, V. de Lapparent, E. Bertin, and D. Le Borgne · 2017
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The redshift distribution of cosmological samples: a forward modeling approach
J. Herbel, T. Kacprzak, A. Amara, A. Refregier, C. Bruderer, and A. Nicola · 2017
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liquidSVM: A Fast and Versatile SVM package
I. Steinwart and P. Thomann · 2017
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