Approximate inference for constructing astronomical catalogs from images

DOI10.1214/19-AOAS1258zbMath1433.62336arXiv1803.00113MaRDI QIDQ2281241

Prabhat, Jon D. McAuliffe, Andrew C. Miller, Ryan P. Adams, David Schlegel, Jeffrey Regier

Publication date: 19 December 2019

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.00113

zbMATH Keywords

high performance computingastronomyMCMCgraphical modelvariational inference

Mathematics Subject Classification ID

Image analysis in multivariate analysis (62H35) Monte Carlo methods (65C05) Applications of statistics to physics (62P35) Statistical astronomy (85A35) Probabilistic graphical models (62H22)

Related Items (2)

Approximate inference for constructing astronomical catalogs from images ⋮ A Bayesian nonparametric approach to super-resolution single-molecule localization

Uses Software

• BayesDA
• Julia
• PMTK
• ASCL
• GitHub
• SExtractor
• GalSim
• SEP
• GaussianMixtures
• The Tractor
• PRMLT

Cites Work

• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Statistical decision theory and Bayesian analysis. 2nd ed
• Slice sampling. (With discussions and rejoinder)
• Inference from iterative simulation using multiple sequences
• Approximate inference for constructing astronomical catalogs from images
• Julia: A Fresh Approach to Numerical Computing
• Variational Bayesian Filtering
• Efficient Variational Bayesian Approximation Method Based on Subspace Optimization
• A Measure-Theoretic Variational Bayesian Algorithm for Large Dimensional Problems
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