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Bayesian Methods for Neural Networks and Related Models

Statistical science, 2004-02, Vol.19 (1), p.128-139

Titterington, D. M.

2004

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Neural Networks: A Review from a Statistical Perspective

Statistical science, 1994-02, Vol.9 (1), p.2-30

1994

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Hierarchical Gaussian process mixtures for regression

Statistics and computing, 2005-01, Vol.15 (1), p.31-41

2005

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Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation

Machine learning, 2003-01, Vol.50 (1-2), p.73-94

2003

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Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2000, Vol.62 (1), p.57-75

2000

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Lack of consistency of mean field and variational Bayes approximations for state space models

Neural processing letters, 2004-11, Vol.20 (3), p.151-170

2004

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Variational Bayes Estimation of Mixing Coefficients

Deterministic and Statistical Methods in Machine Learning, 2005, p.281-295

2005

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Perfect samplers for mixtures of distributions

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2002-01, Vol.64 (4), p.777-790

2002

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Variational approximations for categorical causal modeling with latent variables

Psychometrika, 2003-09, Vol.68 (3), p.391-412

2003

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On the adequacy of variational lower bound functions for likelihood-based inference in Markovian models with missing values

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2002-01, Vol.64 (3), p.549-564

2002

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Parameter estimation for hidden Markov chains

Journal of statistical planning and inference, 2002-11, Vol.108 (1), p.365-390

2002

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Asymptotically optimal difference-based estimation of variance in nonparametric regression

Biometrika, 1990-09, Vol.77 (3), p.521-528

1990

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Computational Bayesian Analysis of Hidden Markov Models

Journal of computational and graphical statistics, 1998-06, Vol.7 (2), p.194-211

1998

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General structure of regularization procedures in image reconstruction

Astronomy and astrophysics (Berlin), 1985-03, Vol.144 (2), p.381-387

TITTERINGTON, D. M

1985

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Recursive Parameter Estimation Using Incomplete Data

Journal of the Royal Statistical Society. Series B, Statistical methodology, 1984-01, Vol.46 (2), p.257-267

Titterington, D. M.

1984

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Convergence controls for MCMC algorithms, with applications to hidden markov chains

Journal of statistical computation and simulation, 1999-11, Vol.64 (4), p.327-355

1999

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Some Methods for Investigating Spatial Clustering, with Epidemiological Applications

Journal of the Royal Statistical Society. Series A, Statistics in society, 1997, Vol.160 (1), p.87-105

1997

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Filtered Gaussian Processes for Learning with Large Data-Sets

Switching and Learning in Feedback Systems, p.128-139

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On the determination of the number of components in a mixture

Statistics & probability letters, 1998-07, Vol.38 (4), p.295-298

1998

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Improving the Mean-Field approximation in belief networks using bahadur's reparameterisation of the multivariate binary distribution

Neural processing letters, 2000-10, Vol.12 (2), p.183-197

2000

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First-order phase transition and bayesian image processing by loopy belief propagation

Progress of theoretical physics. Supplement, 2005, Vol.157 (157), p.288-291

2005

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Probabilistic image processing based on the Q-Ising model by means of the mean-field method and loopy belief propagation

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004, 2004, Vol.2, p.40-43 Vol.2

2004

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On confidence bands in nonparametric density estimation and regression

Journal of multivariate analysis, 1988-10, Vol.27 (1), p.228-254

1988

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The Effect of Simulation Order on Level Accuracy and Power of Monte Carlo Tests

Journal of the Royal Statistical Society. Series B, Statistical methodology, 1989-01, Vol.51 (3), p.459-467

1989

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Observation and modelling of magnetization reversal in multilayers supporting perpendicular magnetization

Journal of physics. D, Applied physics, 1999-02, Vol.32 (4), p.395-403

1999

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Bayesian Methods for Neural Networks and Related Models

Neural Networks: A Review from a Statistical Perspective

Hierarchical Gaussian process mixtures for regression

Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation

Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method

Lack of consistency of mean field and variational Bayes approximations for state space models

Variational Bayes Estimation of Mixing Coefficients

Perfect samplers for mixtures of distributions

Variational approximations for categorical causal modeling with latent variables

On the adequacy of variational lower bound functions for likelihood-based inference in Markovian models with missing values

Parameter estimation for hidden Markov chains

Asymptotically optimal difference-based estimation of variance in nonparametric regression

Computational Bayesian Analysis of Hidden Markov Models

General structure of regularization procedures in image reconstruction

Recursive Parameter Estimation Using Incomplete Data

Convergence controls for MCMC algorithms, with applications to hidden markov chains

Some Methods for Investigating Spatial Clustering, with Epidemiological Applications

Filtered Gaussian Processes for Learning with Large Data-Sets

On the determination of the number of components in a mixture

Improving the Mean-Field approximation in belief networks using bahadur's reparameterisation of the multivariate binary distribution

First-order phase transition and bayesian image processing by loopy belief propagation

Probabilistic image processing based on the Q-Ising model by means of the mean-field method and loopy belief propagation

On confidence bands in nonparametric density estimation and regression

The Effect of Simulation Order on Level Accuracy and Power of Monte Carlo Tests

Observation and modelling of magnetization reversal in multilayers supporting perpendicular magnetization

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