| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields
|
Stoehr, Julien
|
|
2014
|
25 |
1 |
p. 129-141
|
artikel
|
| 2 |
An introduction to the special issue “Joint IMS-ISBA meeting - MCMSki 4”
|
Mira, Antonietta
|
|
2014
|
25 |
1 |
p. 1
|
artikel
|
| 3 |
Cuts in Bayesian graphical models
|
Plummer, Martyn
|
|
2014
|
25 |
1 |
p. 37-43
|
artikel
|
| 4 |
Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks
|
Caimo, Alberto
|
|
2014
|
25 |
1 |
p. 113-125
|
artikel
|
| 5 |
Efficient local updates for undirected graphical models
|
Stingo, Francesco
|
|
2014
|
25 |
1 |
p. 159-171
|
artikel
|
| 6 |
Fast matrix computations for functional additive models
|
Barthelmé, Simon
|
|
2014
|
25 |
1 |
p. 47-63
|
artikel
|
| 7 |
Introduction to “Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields” by J. Stoehr, P. Pudlo, L. Cucala
|
Robert, Christian P.
|
|
2014
|
25 |
1 |
p. 127
|
artikel
|
| 8 |
Introduction to “Cuts in Bayesian graphical models” by M. Plummer
|
Carlin, Bradley
|
|
2014
|
25 |
1 |
p. 35
|
artikel
|
| 9 |
Introduction to “Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks” by A. Caimo, A. Mira
|
Friel, Nial
|
|
2014
|
25 |
1 |
p. 111
|
artikel
|
| 10 |
Introduction to “Efficient local updates for undirected graphical models” by F. Stingo, G. Marchetti
|
Fox, Colin
|
|
2014
|
25 |
1 |
p. 157
|
artikel
|
| 11 |
Introduction to “Fast matrix computations for functional additive models” by S. Barthelmé
|
Rue, Håvard
|
|
2014
|
25 |
1 |
p. 45
|
artikel
|
| 12 |
Introduction to “On a class of $$\sigma $$σ-stable Poisson–Kingman models and an effective marginalized sampler” by S. Favaro, M. Lomeli, Y. W. Teh
|
Mueller, Peter
|
|
2014
|
25 |
1 |
p. 65-66
|
artikel
|
| 13 |
Introduction to “On the use of Markov chain Monte Carlo methods for the sampling of mixture models” by R. Douc, F. Maire, J. Olsson
|
Peluso, Stefano
|
|
2014
|
25 |
1 |
p. 93-94
|
artikel
|
| 14 |
Introduction to “Particle Metropolis-Hastings using gradient and Hessian information” by J. Dahlin, F. Lindsten, T. Schön
|
Andrieu, Christophe
|
|
2014
|
25 |
1 |
p. 79
|
artikel
|
| 15 |
Introduction to “Pre-processing for approximate Bayesian computation in image analysis” by M. Moores, C. Drovandi, K. Mengersen, C. Robert
|
Friel, Nial
|
|
2014
|
25 |
1 |
p. 21
|
artikel
|
| 16 |
Introduction to “Quantitative bounds of convergence for geometrically ergodic Markov Chain in the Wasserstein distance with application to the Metropolis adjusted Langevin algorithm” by A. Durmus, É. Moulines
|
Haario, Heikki
|
|
2014
|
25 |
1 |
p. 3
|
artikel
|
| 17 |
Introduction to “Scalable inference for Markov processes with intractable likelihoods” by J. Owen, D. Wilkinson, C. Gillespie
|
Ryder, Robin J.
|
|
2014
|
25 |
1 |
p. 143
|
artikel
|
| 18 |
On a class of $$\sigma $$σ-stable Poisson–Kingman models and an effective marginalized sampler
|
Favaro, S.
|
|
2014
|
25 |
1 |
p. 67-78
|
artikel
|
| 19 |
On the use of Markov chain Monte Carlo methods for the sampling of mixture models: a statistical perspective
|
Douc, Randal
|
|
2014
|
25 |
1 |
p. 95-110
|
artikel
|
| 20 |
Particle Metropolis–Hastings using gradient and Hessian information
|
Dahlin, Johan
|
|
2014
|
25 |
1 |
p. 81-92
|
artikel
|
| 21 |
Pre-processing for approximate Bayesian computation in image analysis
|
Moores, Matthew T.
|
|
2014
|
25 |
1 |
p. 23-33
|
artikel
|
| 22 |
Quantitative bounds of convergence for geometrically ergodic Markov chain in the Wasserstein distance with application to the Metropolis Adjusted Langevin Algorithm
|
Durmus, Alain
|
|
2014
|
25 |
1 |
p. 5-19
|
artikel
|
| 23 |
Scalable inference for Markov processes with intractable likelihoods
|
Owen, Jamie
|
|
2014
|
25 |
1 |
p. 145-156
|
artikel
|
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