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Expectation Propagation for approximate Bayesian inference

Expectation Propagation for approximate Bayesian inference

10 January 2013
T. Minka
ArXivPDFHTML

Papers citing "Expectation Propagation for approximate Bayesian inference"

50 / 491 papers shown
Title
Streaming Variational Inference for Bayesian Nonparametric Mixture
  Models
Streaming Variational Inference for Bayesian Nonparametric Mixture Models
Alex Tank
N. Foti
E. Fox
BDL
21
37
0
01 Dec 2014
Robust EM kernel-based methods for linear system identification
Robust EM kernel-based methods for linear system identification
Giulio Bottegal
Aleksandr Aravkin
H. Hjalmarsson
G. Pillonetto
31
50
0
21 Nov 2014
Bayesian Evidence and Model Selection
Bayesian Evidence and Model Selection
K. Knuth
Michael Habeck
N. Malakar
Asim M. Mubeen
Ben Placek
BDL
26
96
0
11 Nov 2014
Computation of Gaussian orthant probabilities in high dimension
Computation of Gaussian orthant probabilities in high dimension
James Ridgway
24
22
0
05 Nov 2014
Projecting Markov Random Field Parameters for Fast Mixing
Projecting Markov Random Field Parameters for Fast Mixing
Xianghang Liu
Justin Domke
24
6
0
05 Nov 2014
A* Sampling
A* Sampling
Chris J. Maddison
Daniel Tarlow
T. Minka
29
391
0
31 Oct 2014
Consensus Message Passing for Layered Graphical Models
Consensus Message Passing for Layered Graphical Models
Varun Jampani
S. M. Ali Eslami
Daniel Tarlow
Pushmeet Kohli
J. Winn
28
4
0
27 Oct 2014
PAC-Bayesian AUC classification and scoring
PAC-Bayesian AUC classification and scoring
James Ridgway
Pierre Alquier
Nicolas Chopin
Feng Liang
40
21
0
07 Oct 2014
Expectation Propagation
Expectation Propagation
Jack Raymond
Andre Manoel
Manfred Opper
GAN
VLM
34
1
0
22 Sep 2014
SAME but Different: Fast and High-Quality Gibbs Parameter Estimation
SAME but Different: Fast and High-Quality Gibbs Parameter Estimation
Huasha Zhao
Biye Jiang
John F. Canny
13
34
0
18 Sep 2014
Approximate Inference for Nonstationary Heteroscedastic Gaussian process
  Regression
Approximate Inference for Nonstationary Heteroscedastic Gaussian process Regression
Ville Tolvanen
Pasi Jylänki
Aki Vehtari
44
60
0
22 Apr 2014
Exploiting the Statistics of Learning and Inference
Exploiting the Statistics of Learning and Inference
Max Welling
34
5
0
26 Feb 2014
Fast matrix computations for functional additive models
Fast matrix computations for functional additive models
Simon Barthelmé
22
3
0
20 Feb 2014
Efficient Gradient-Based Inference through Transformations between Bayes
  Nets and Neural Nets
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets
Diederik P. Kingma
Max Welling
BDL
36
61
0
03 Feb 2014
Nonparametric Latent Tree Graphical Models: Inference, Estimation, and
  Structure Learning
Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning
Le Song
Han Liu
Ankur P. Parikh
Eric P. Xing
63
9
0
16 Jan 2014
Bayesian Conditional Density Filtering
Bayesian Conditional Density Filtering
S. Qamar
Rajarshi Guhaniyogi
David B. Dunson
45
11
0
15 Jan 2014
Join-Graph Propagation Algorithms
Join-Graph Propagation Algorithms
R. Mateescu
Kalev Kask
Vibhav Gogate
R. Dechter
32
70
0
15 Jan 2014
Approximate Bayesian Computation for a Class of Time Series Models
Approximate Bayesian Computation for a Class of Time Series Models
Ajay Jasra
AI4TS
26
30
0
01 Jan 2014
Using Latent Binary Variables for Online Reconstruction of Large Scale
  Systems
Using Latent Binary Variables for Online Reconstruction of Large Scale Systems
Victorin Martin
Jean-Marc Lasgouttes
Cyril Furtlehner
24
4
0
23 Dec 2013
Time-varying Learning and Content Analytics via Sparse Factor Analysis
Time-varying Learning and Content Analytics via Sparse Factor Analysis
Andrew S. Lan
Christoph Studer
Richard G. Baraniuk
42
61
0
19 Dec 2013
Detecting Parameter Symmetries in Probabilistic Models
Detecting Parameter Symmetries in Probabilistic Models
Robert Nishihara
T. Minka
Daniel Tarlow
34
18
0
19 Dec 2013
Online Bayesian Passive-Aggressive Learning
Online Bayesian Passive-Aggressive Learning
Tianlin Shi
Jun Zhu
61
38
0
12 Dec 2013
Expectation Propagation for Nonlinear Inverse Problems -- with an
  Application to Electrical Impedance Tomography
Expectation Propagation for Nonlinear Inverse Problems -- with an Application to Electrical Impedance Tomography
M. Gehre
Bangti Jin
48
26
0
12 Dec 2013
Bayesian Inference for Gaussian Process Classifiers with Annealing and
  Pseudo-Marginal MCMC
Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC
Maurizio Filippone
31
6
0
28 Nov 2013
Approximate Bayesian Computation with composite score functions
Approximate Bayesian Computation with composite score functions
E. Ruli
Nicola Sartori
L. Ventura
34
35
0
28 Nov 2013
On the use of marginal posteriors in marginal likelihood estimation via
  importance-sampling
On the use of marginal posteriors in marginal likelihood estimation via importance-sampling
K. Perrakis
I. Ntzoufras
E. Tsionas
35
67
0
04 Nov 2013
Mean Field Bayes Backpropagation: scalable training of multilayer neural
  networks with binary weights
Mean Field Bayes Backpropagation: scalable training of multilayer neural networks with binary weights
Daniel Soudry
Ron Meir
35
4
0
07 Oct 2013
Pseudo-Marginal Bayesian Inference for Gaussian Processes
Pseudo-Marginal Bayesian Inference for Gaussian Processes
Maurizio Filippone
Mark Girolami
36
64
0
02 Oct 2013
Structured Message Passing
Structured Message Passing
Vibhav Gogate
Pedro M. Domingos
TPM
28
20
0
26 Sep 2013
Measure Transformer Semantics for Bayesian Machine Learning
Measure Transformer Semantics for Bayesian Machine Learning
J. Borgström
Andrew D. Gordon
Michael Greenberg
J. Margetson
Jurgen Van Gael
38
104
0
03 Aug 2013
Streaming Variational Bayes
Streaming Variational Bayes
Tamara Broderick
N. Boyd
Andre Wibisono
Ashia C. Wilson
Michael I. Jordan
38
342
0
25 Jul 2013
Gaussian Process Conditional Copulas with Applications to Financial Time
  Series
Gaussian Process Conditional Copulas with Applications to Financial Time Series
José Miguel Hernández-Lobato
J. Lloyd
Daniel Hernández-Lobato
61
18
0
01 Jul 2013
Fast Dual Variational Inference for Non-Conjugate LGMs
Fast Dual Variational Inference for Non-Conjugate LGMs
Mohammad Emtiyaz Khan
Aleksandr Aravkin
M. Friedlander
Matthias Seeger
BDL
31
4
0
05 Jun 2013
Fast Gradient-Based Inference with Continuous Latent Variable Models in
  Auxiliary Form
Fast Gradient-Based Inference with Continuous Latent Variable Models in Auxiliary Form
Diederik P. Kingma
36
40
0
04 Jun 2013
Declarative Modeling and Bayesian Inference of Dark Matter Halos
Declarative Modeling and Bayesian Inference of Dark Matter Halos
G. Kronberger
59
0
0
02 Jun 2013
Expectation Propagation for Neural Networks with Sparsity-promoting
  Priors
Expectation Propagation for Neural Networks with Sparsity-promoting Priors
Pasi Jylänki
A. Nummenmaa
Aki Vehtari
36
36
0
27 Mar 2013
A dependent partition-valued process for multitask clustering and time
  evolving network modelling
A dependent partition-valued process for multitask clustering and time evolving network modelling
Konstantina Palla
David A. Knowles
Zoubin Ghahramani
53
3
0
13 Mar 2013
Gaussian Processes for Nonlinear Signal Processing
Gaussian Processes for Nonlinear Signal Processing
Fernando Perez-Cruz
S. Van Vaerenbergh
J. J. Murillo-Fuentes
Miguel Lazaro-Gredilla
I. Santamaría
GP
41
152
0
12 Mar 2013
Gaussian Process Vine Copulas for Multivariate Dependence
Gaussian Process Vine Copulas for Multivariate Dependence
David Lopez-Paz
José Miguel Hernández-Lobato
Zoubin Ghahramani
31
44
0
16 Feb 2013
Fast Approximate Bayesian Computation for discretely observed Markov
  models using a factorised posterior distribution
Fast Approximate Bayesian Computation for discretely observed Markov models using a factorised posterior distribution
S. White
T. Kypraios
S. Preston
34
7
0
14 Jan 2013
Perturbative Corrections for Approximate Inference in Gaussian Latent
  Variable Models
Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models
Manfred Opper
Ulrich Paquet
Ole Winther
39
14
0
12 Jan 2013
Heteroscedastic Relevance Vector Machine
Heteroscedastic Relevance Vector Machine
Daniel Khashabi
Mojtaba Ziyadi
Feng Liang
BDL
56
5
0
10 Jan 2013
Decayed MCMC Filtering
Decayed MCMC Filtering
B. Marthi
H. Pasula
Stuart J. Russell
Yuval Peres
34
33
0
12 Dec 2012
Expectation Propogation for approximate inference in dynamic Bayesian
  networks
Expectation Propogation for approximate inference in dynamic Bayesian networks
Tom Heskes
O. Zoeter
31
130
0
12 Dec 2012
A Generalized Mean Field Algorithm for Variational Inference in
  Exponential Families
A Generalized Mean Field Algorithm for Variational Inference in Exponential Families
Eric P. Xing
Michael I. Jordan
Stuart J. Russell
31
251
0
19 Oct 2012
Variational Inference in Nonconjugate Models
Variational Inference in Nonconjugate Models
Chong-Jun Wang
David M. Blei
BDL
44
227
0
19 Sep 2012
Expectation Propagation in Gaussian Process Dynamical Systems: Extended
  Version
Expectation Propagation in Gaussian Process Dynamical Systems: Extended Version
M. Deisenroth
S. Mohamed
39
45
0
12 Jul 2012
On the Choice of Regions for Generalized Belief Propagation
On the Choice of Regions for Generalized Belief Propagation
Max Welling
33
75
0
11 Jul 2012
Structured Region Graphs: Morphing EP into GBP
Structured Region Graphs: Morphing EP into GBP
Max Welling
T. Minka
Yee Whye Teh
37
46
0
04 Jul 2012
Sufficient conditions for convergence of Loopy Belief Propagation
Sufficient conditions for convergence of Loopy Belief Propagation
Joris Mooij
H. Kappen
47
65
0
04 Jul 2012
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