Keyword

posterior sampling

Description: A computational method for drawing samples from a Bayesian posterior distribution to represent uncertainty about parameters or latent variables given observed data.

Primary topic: Markov Chains and Monte Carlo Methods (32%)

OpenAlex ID: keywords/posterior-sampling

Markov Chains for Exploring Posterior Distributions

1994 · Luke Tierney · The Annals of Statistics · 3,461

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MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics

2009 · F. Feroz, M. P. Hobson, et al. · Monthly Notices of the Royal Astronomical Society · 2,962

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MCMC Using Hamiltonian Dynamics

2011 · Radford M. Neal · Chapman & Hall/CRC eBooks · 2,575

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Explaining the Gibbs Sampler

1992 · George Casella, Edward I. George · The American Statistician · 2,424

Markov Chain Sampling Methods for Dirichlet Process Mixture Models

2000 · Radford M. Neal · Journal of Computational and Graphical Statistics · 2,290

Nested sampling for general Bayesian computation

2006 · John Skilling · Bayesian Analysis · 1,670

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Gibbs Sampling Methods for Stick-Breaking Priors

2001 · Hemant Ishwaran, Lancelot F James · Journal of the American Statistical Association · 1,515

Bayesian Learning via Stochastic Gradient Langevin Dynamics

2012 · Max Welling, Yee Whye Teh · 1,500

Markov chain Monte Carlo without likelihoods

2003 · Paul Marjoram, John Molitor, et al. · Proceedings of the National Academy of Sciences · 1,198

Bayesian statistics and modelling

2021 · Rens van de Schoot, Sarah Depaoli, et al. · Nature Reviews Methods Primers · 1,178

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The Art of Data Augmentation

2001 · David A van Dyk, Xiao-Li Meng · Journal of Computational and Graphical Statistics · 1,053

Nested Sampling

2004 · John Skilling · AIP conference proceedings · 953

Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables

2013 · Nicholas G. Polson, James G. Scott, et al. · Journal of the American Statistical Association · 934

Monte Carlo Methods in Bayesian Computation

2000 · Ming-Hui Chen, Qi-Man Shao, et al. · Springer series in statistics · 911

Markov chain Monte Carlo simulation using the DREAM software package: Theory, concepts, and MATLAB implementation

2015 · Jasper A. Vrugt · Environmental Modelling & Software · 852

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PyMC: Bayesian Stochastic Modelling inPython

2010 · Anand Patil, David Huard, et al. · Journal of Statistical Software · 709

RadVel: The Radial Velocity Modeling Toolkit

2018 · Benjamin J. Fulton, Erik A. Petigura, et al. · Publications of the Astronomical Society of the Pacific · 537

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polychord : nested sampling for cosmology

2015 · W. J. Handley, M. P. Hobson, et al. · Monthly Notices of the Royal Astronomical Society Letters · 506

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polychord: next-generation nested sampling

2015 · W. J. Handley, M. P. Hobson, et al. · Monthly Notices of the Royal Astronomical Society · 503

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Learning to Optimize via Posterior Sampling

2014 · Daniel Russo, Benjamin Van Roy · Mathematics of Operations Research · 494

Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology

2008 · Andrew Lawson · Thammasat University Digital Collections · 436

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables

2019 · Rakelly, Kate, Zhou, Aurick, et al. · arXiv (Cornell University) · 371

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Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models

2008 · O. Papaspiliopoulos, G. O. Roberts · Biometrika · 352

An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants

2006 · J. Møller, A. N. Pettitt, et al. · Biometrika · 352

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Markov Chain Monte Carlo Simulations and Their Statistical Analysis

2004 · Bernd A Berg · WORLD SCIENTIFIC eBooks · 343

Works count: 2,921

Citation count: 58,540