Keyword

posterior approximation

Description: Posterior approximation is a computational method for representing or estimating a Bayesian posterior distribution when exact inference is impractical.

Primary topic: Markov Chains and Monte Carlo Methods (24%)

OpenAlex ID: keywords/posterior-approximation

Variational Inference: A Review for Statisticians

2017 · David M. Blei, Alp Kucukelbir, et al. · Journal of the American Statistical Association · 3,925

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Stochastic variational inference

2013 · Matthew D. Hoffman, David M. Blei, et al. · Journal of Machine Learning Research · 1,801

Bayesian Inference in Econometric Models Using Monte Carlo Integration

1989 · John Geweke · Econometrica · 1,563

The Unscented Particle Filter

2000 · Rudolph van der Merwe, Arnaud Doucet, et al. · 1,396

Bayesian Data Analysis

2014 · Paul Hewson · Journal of the Royal Statistical Society Series A (Statistics in Society) · 1,367

Auto-Encoding Variational Bayes

2024 · Yankun Chen, Jingxuan Liu, et al. · Cambridge Explorations in Arts and Sciences · 938

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A survey of convergence results on particle filtering methods for practitioners

2002 · D. Crisan, A. Doucet · IEEE Transactions on Signal Processing · 919

Estimation of Finite Mixture Distributions Through Bayesian Sampling

1994 · Jean Diebolt, Christian P. Robert · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 912

Correlated Topic Models

2005 · John Lafferty, David M. Blei · neural information processing systems · 903

A family of algorithms for approximate bayesian inference

2001 · Thomas P. Minka, Rosalind W. Picard · DSpace@MIT (Massachusetts Institute of Technology) · 877

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Stochastic Variational Inference

2012 · Hoffman, Matt, Blei, David M., et al. · arXiv (Cornell University) · 850

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Black Box Variational Inference

2013 · Ranganath, Rajesh, Gerrish, Sean, et al. · arXiv (Cornell University) · 646

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Importance Weighted Autoencoders

2015 · Burda, Yuri, Grosse, Roger, et al. · arXiv (Cornell University) · 644

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Discrete-Time Nonlinear Filtering Algorithms Using Gauss–Hermite Quadrature

2007 · Ienkaran Arasaratnam, Simon Haykin, et al. · Proceedings of the IEEE · 624

Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference

2015 · Gal, Yarin, Ghahramani, Zoubin · arXiv (Cornell University) · 595

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Covariance Structure of the Gibbs Sampler with Applications to the Comparisons of Estimators and Augmentation Schemes

1994 · J. S. LIU, W. H. WONG, et al. · Biometrika · 542

Recursive Bayesian Estimation : Navigation and Tracking Applications

1999 · Niclas Bergman · 529

Inferring Parameters and Structure of Latent Variable Models by Variational Bayes

2013 · Attias, Hagai · arXiv (Cornell University) · 526

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Variational Bayesian Inference for a Nonlinear Forward Model

2008 · M.A. Chappell, A.R. Groves, et al. · IEEE Transactions on Signal Processing · 482

Evaluating Pharmacokinetic/Pharmacodynamic Models Using the Posterior Predictive Check

2001 · Yoshitaka Yano, Stuart L. Beal, et al. · Journal of Pharmacokinetics and Pharmacodynamics · 407

Markov Chain Monte Carlo and Variational Inference: Bridging the Gap

2014 · Salimans, Tim, Kingma, Diederik P., et al. · UvA-DARE (University of Amsterdam) · 368

Structured Inference Networks for Nonlinear State Space Models

2017 · Krishnan, Rahul, Shalit, Uri, et al. · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) · 355

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Approximating Posterior Distributions by Mixtures

1993 · Mike West · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 337

The Variational Gaussian Approximation Revisited

2008 · Manfred Opper, Cédric Archambeau · Neural Computation · 293

Variational principal components

1999 · C.M. Bishop · 280

Works count: 1,851

Citation count: 45,280