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Approximate Bayesian Computational methods

Approximate Bayesian Computational methods

5 January 2011
Jean-Michel Marin
Pierre Pudlo
Christian P. Robert
Robin J. Ryder
ArXivPDFHTML

Papers citing "Approximate Bayesian Computational methods"

50 / 254 papers shown
Title
Inference via low-dimensional couplings
Inference via low-dimensional couplings
Alessio Spantini
Daniele Bigoni
Youssef Marzouk
38
119
0
17 Mar 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Hierarchical Implicit Models and Likelihood-Free Variational Inference
Dustin Tran
Rajesh Ranganath
David M. Blei
VLM
GAN
30
100
0
28 Feb 2017
Multilevel rejection sampling for approximate Bayesian computation
Multilevel rejection sampling for approximate Bayesian computation
D. Warne
R. Baker
Matthew J. Simpson
17
28
0
10 Feb 2017
Query Efficient Posterior Estimation in Scientific Experiments via
  Bayesian Active Learning
Query Efficient Posterior Estimation in Scientific Experiments via Bayesian Active Learning
Kirthevasan Kandasamy
J. Schneider
Barnabás Póczós
20
29
0
03 Feb 2017
Modelling Preference Data with the Wallenius Distribution
Modelling Preference Data with the Wallenius Distribution
Clara Grazian
Fabrizio Leisen
B. Liseo
21
2
0
27 Jan 2017
Bayesian Inference in the Presence of Intractable Normalizing Functions
Bayesian Inference in the Presence of Intractable Normalizing Functions
Jaewoo Park
M. Haran
TPM
33
71
0
23 Jan 2017
On parameter estimation with the Wasserstein distance
On parameter estimation with the Wasserstein distance
Espen Bernton
H. Shakespeare
Mathieu Gerber
Christian P. Robert
39
77
0
18 Jan 2017
Likelihood-free inference by ratio estimation
Likelihood-free inference by ratio estimation
Owen Thomas
Ritabrata Dutta
J. Corander
Samuel Kaski
Michael U. Gutmann
42
145
0
30 Nov 2016
A rare event approach to high dimensional Approximate Bayesian
  computation
A rare event approach to high dimensional Approximate Bayesian computation
D. Prangle
R. Everitt
T. Kypraios
21
22
0
08 Nov 2016
Estimating the marginal likelihood with Integrated nested Laplace
  approximation (INLA)
Estimating the marginal likelihood with Integrated nested Laplace approximation (INLA)
A. Hubin
G. Storvik
24
21
0
04 Nov 2016
Gaussian process modeling in approximate Bayesian computation to
  estimate horizontal gene transfer in bacteria
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
Marko Jarvenpaa
Michael U. Gutmann
Aki Vehtari
Pekka Marttinen
37
41
0
20 Oct 2016
Learning in Implicit Generative Models
Learning in Implicit Generative Models
S. Mohamed
Balaji Lakshminarayanan
GAN
25
412
0
11 Oct 2016
Likelihood-free stochastic approximation EM for inference in complex
  models
Likelihood-free stochastic approximation EM for inference in complex models
Umberto Picchini
TPM
19
5
0
12 Sep 2016
Bayesian nonparametric forecasting of monotonic functional time series
Bayesian nonparametric forecasting of monotonic functional time series
A. Canale
M. Ruggiero
AI4TS
31
23
0
29 Aug 2016
Using Approximate Bayesian Computation by Subset Simulation for
  Efficient Posterior Assessment of Dynamic State-Space Model Classes
Using Approximate Bayesian Computation by Subset Simulation for Efficient Posterior Assessment of Dynamic State-Space Model Classes
M. Vakilzadeh
J. Beck
T. Abrahamsson
17
14
0
04 Aug 2016
Bayesian inference for stochastic differential equation mixed effects
  models of a tumor xenography study
Bayesian inference for stochastic differential equation mixed effects models of a tumor xenography study
Umberto Picchini
J. Forman
39
23
0
09 Jul 2016
Applications of Probabilistic Programming (Master's thesis, 2015)
Applications of Probabilistic Programming (Master's thesis, 2015)
Yura N. Perov
23
4
0
31 May 2016
Asymptotically exact inference in differentiable generative models
Asymptotically exact inference in differentiable generative models
Matthew M. Graham
Amos J. Storkey
BDL
21
33
0
25 May 2016
ABC random forests for Bayesian parameter inference
ABC random forests for Bayesian parameter inference
Louis Raynal
Jean-Michel Marin
Pierre Pudlo
M. Ribatet
Christian P. Robert
A. Estoup
32
187
0
18 May 2016
An ABC interpretation of the multiple auxiliary variable method
An ABC interpretation of the multiple auxiliary variable method
D. Prangle
R. Everitt
17
0
0
27 Apr 2016
Approximate Bayesian Computation and Model Validation for Repulsive
  Spatial Point Processes
Approximate Bayesian Computation and Model Validation for Repulsive Spatial Point Processes
Shinichiro Shirota
A. Gelfand
28
14
0
24 Apr 2016
Mode jumping MCMC for Bayesian variable selection in GLMM
Mode jumping MCMC for Bayesian variable selection in GLMM
A. Hubin
G. Storvik
20
28
0
21 Apr 2016
Some comments about James Watson's and Chris Holmes' "Approximate Models
  and Robust Decisions": Nonparametric Bayesian clay for robust decision bricks
Some comments about James Watson's and Chris Holmes' "Approximate Models and Robust Decisions": Nonparametric Bayesian clay for robust decision bricks
Christian P. Robert
Judith Rousseau
AAML
18
1
0
30 Mar 2016
An introduction to sampling via measure transport
An introduction to sampling via measure transport
Youssef Marzouk
Tarek A. El-Moselhy
M. Parno
Alessio Spantini
OT
38
88
0
16 Feb 2016
Hidden Gibbs random fields model selection using Block Likelihood
  Information Criterion
Hidden Gibbs random fields model selection using Block Likelihood Information Criterion
Julien Stoehr
Jean-Michel Marin
Pierre Pudlo
18
3
0
08 Feb 2016
Coupling stochastic EM and Approximate Bayesian Computation for
  parameter inference in state-space models
Coupling stochastic EM and Approximate Bayesian Computation for parameter inference in state-space models
Umberto Picchini
Adeline M. M. Samson
11
17
0
15 Dec 2015
Accelerating pseudo-marginal Metropolis-Hastings by correlating
  auxiliary variables
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables
J. Dahlin
Fredrik Lindsten
J. Kronander
Thomas B. Schon
30
37
0
17 Nov 2015
Getting Started with Particle Metropolis-Hastings for Inference in
  Nonlinear Dynamical Models
Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models
J. Dahlin
Thomas B. Schon
23
25
0
05 Nov 2015
Learning Summary Statistic for Approximate Bayesian Computation via Deep
  Neural Network
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network
Bai Jiang
Tung-Yu Wu
Charles Yang Zheng
W. Wong
BDL
26
140
0
08 Oct 2015
A Simulated Annealing Approach to Bayesian Inference
A Simulated Annealing Approach to Bayesian Inference
Carlo Albert
18
3
0
17 Sep 2015
Boosting Bayesian Parameter Inference of Nonlinear Stochastic
  Differential Equation Models by Hamiltonian Scale Separation
Boosting Bayesian Parameter Inference of Nonlinear Stochastic Differential Equation Models by Hamiltonian Scale Separation
Carlo Albert
S. Ulzega
R. Stoop
20
13
0
17 Sep 2015
On the contraction properties of some high-dimensional quasi-posterior
  distributions
On the contraction properties of some high-dimensional quasi-posterior distributions
Yves F. Atchadé
18
39
0
31 Aug 2015
Optimal approximating Markov chains for Bayesian inference
Optimal approximating Markov chains for Bayesian inference
J. Johndrow
Jonathan C. Mattingly
Sayan Mukherjee
David B. Dunson
25
31
0
13 Aug 2015
ABC Shadow algorithm: a tool for statistical analysis of spatial
  patterns
ABC Shadow algorithm: a tool for statistical analysis of spatial patterns
R. Stoica
A. Philippe
P. Gregori
J. Mateu
26
13
0
15 Jul 2015
Adapting the ABC distance function
Adapting the ABC distance function
D. Prangle
32
94
0
03 Jul 2015
Spectral likelihood expansions for Bayesian inference
Spectral likelihood expansions for Bayesian inference
J. Nagel
Bruno Sudret
22
40
0
24 Jun 2015
Bayesian optimisation for fast approximate inference in state-space
  models with intractable likelihoods
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
J. Dahlin
M. Villani
Thomas B. Schon
21
6
0
23 Jun 2015
Three discussions of the paper "sequential quasi-Monte Carlo sampling",
  by M. Gerber and N. Chopin
Three discussions of the paper "sequential quasi-Monte Carlo sampling", by M. Gerber and N. Chopin
Mathieu Gerber
Igor Prunster
N. Chopin
Robin J. Ryder
31
69
0
24 May 2015
Approximate maximum likelihood estimation using data-cloning ABC
Approximate maximum likelihood estimation using data-cloning ABC
Umberto Picchini
Rachele Anderson
28
13
0
23 May 2015
Sequential Bayesian inference for implicit hidden Markov models and
  current limitations
Sequential Bayesian inference for implicit hidden Markov models and current limitations
Pierre E. Jacob
36
15
0
16 May 2015
Scalable Bayesian Inference for the Inverse Temperature of a Hidden
  Potts Model
Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model
M. Moores
Geoff K. Nicholls
A. Pettitt
Kerrie Mengersen
TPM
35
22
0
27 Mar 2015
Perturbation theory for Markov chains via Wasserstein distance
Perturbation theory for Markov chains via Wasserstein distance
Daniel Rudolf
Nikolaus Schweizer
40
107
0
13 Mar 2015
Approximate Bayesian inference in semiparametric copula models
Approximate Bayesian inference in semiparametric copula models
Clara Grazian
B. Liseo
31
21
0
10 Mar 2015
Hamiltonian ABC
Hamiltonian ABC
Edward Meeds
R. Leenders
Max Welling
BDL
43
31
0
06 Mar 2015
Quasi-Newton particle Metropolis-Hastings
Quasi-Newton particle Metropolis-Hastings
J. Dahlin
Fredrik Lindsten
Thomas B. Schon
27
9
0
12 Feb 2015
Some comments about A. Ronald Gallant's "Reflections on the Probability
  Space Induced by Moment Conditions with Implications for Bayesian Inference"
Some comments about A. Ronald Gallant's "Reflections on the Probability Space Induced by Moment Conditions with Implications for Bayesian Inference"
Christian P. Robert
30
1
0
05 Feb 2015
Bayesian computation: a perspective on the current state, and sampling
  backwards and forwards
Bayesian computation: a perspective on the current state, and sampling backwards and forwards
P. Green
K. Latuszyñski
Marcelo Pereyra
Christian P. Robert
50
21
0
04 Feb 2015
Lazier ABC
Lazier ABC
D. Prangle
21
2
0
21 Jan 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based
  Statistical Models
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models
Michael U. Gutmann
J. Corander
40
285
0
14 Jan 2015
Gibbs posterior inference on the minimum clinically important difference
Gibbs posterior inference on the minimum clinically important difference
Nicholas Syring
Ryan Martin
29
17
0
08 Jan 2015
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