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Iterated filtering
v1v2 (latest)

Iterated filtering

2 February 2009
E. Ionides
A. Bhadra
Yves F. Atchadé
A. King
ArXiv (abs)PDFHTML

Papers citing "Iterated filtering"

25 / 25 papers shown
Gradient-free optimization via integration
Gradient-free optimization via integration
Christophe Andrieu
N. Chopin
Ettore Fincato
Mathieu Gerber
172
1
0
01 Aug 2024
Normalizing Flow-based Differentiable Particle Filters
Normalizing Flow-based Differentiable Particle Filters
Xiongjie Chen
Yunpeng Li
260
0
0
03 Mar 2024
Voronoi Candidates for Bayesian Optimization
Voronoi Candidates for Bayesian Optimization
Nathan Wycoff
John W. Smith
Annie S. Booth
R. Gramacy
317
4
0
07 Feb 2024
Consistent and fast inference in compartmental models of epidemics using
  Poisson Approximate Likelihoods
Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods
M. Whitehouse
N. Whiteley
Lorenzo Rimella
271
12
0
26 May 2022
Iterated Block Particle Filter for High-dimensional Parameter Learning:
  Beating the Curse of Dimensionality
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of DimensionalityJournal of machine learning research (JMLR), 2021
Ning Ning
E. Ionides
388
20
0
20 Oct 2021
Systemic Infinitesimal Over-dispersion on Graphical Dynamic Models
Systemic Infinitesimal Over-dispersion on Graphical Dynamic ModelsStatistics and computing (Stat Comput), 2021
Ning Ning
E. Ionides
230
1
0
18 Jun 2021
Moving-Resting Process with Measurement Error in Animal Movement
  Modeling
Moving-Resting Process with Measurement Error in Animal Movement ModelingMethods in Ecology and Evolution (Methods Ecol. Evol.), 2020
Chaoran Hu
Mark Elbroch
T. Meyer
V. Pozdnyakov
Jun Yan
220
4
0
31 Mar 2020
Simulation-based inference methods for partially observed Markov model
  via the R package is2
Simulation-based inference methods for partially observed Markov model via the R package is2
Bernhard Bergmair
Johann Hoffelner
Siegfried Silber
374
0
0
07 Nov 2018
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear
  Bayesian Filtering: A New Perspective
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective
Filip Tronarp
Hans Kersting
Simo Särkkä
Philipp Hennig
362
74
0
08 Oct 2018
A critical analysis of resampling strategies for the regularized
  particle filter
A critical analysis of resampling strategies for the regularized particle filter
Pierre Carmier
Olexiy O. Kyrgyzov
P. Cournède
162
3
0
11 May 2017
Efficient data augmentation for fitting stochastic epidemic models to
  prevalence data
Efficient data augmentation for fitting stochastic epidemic models to prevalence dataJournal of Computational And Graphical Statistics (JCGS), 2016
J. Fintzi
Xiang Cui
J. Wakefield
V. Minin
170
37
0
26 Jun 2016
On Coupling Particle Filter Trajectories
On Coupling Particle Filter TrajectoriesStatistics and computing (Stat. Comput.), 2016
Deborshee Sen
Alexandre Hoang Thiery
Ajay Jasra
418
22
0
03 Jun 2016
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
260
16
0
16 May 2015
On Particle Methods for Parameter Estimation in State-Space Models
On Particle Methods for Parameter Estimation in State-Space Models
N. Kantas
Arnaud Doucet
Sumeetpal S. Singh
J. Maciejowski
Nicolas Chopin
518
469
0
30 Dec 2014
Particle Metropolis-adjusted Langevin algorithms
Particle Metropolis-adjusted Langevin algorithms
Christopher Nemeth
Chris Sherlock
Paul Fearnhead
462
25
0
23 Dec 2014
Sequential Bayesian inference for static parameters in dynamic state
  space models
Sequential Bayesian inference for static parameters in dynamic state space models
Arnab Bhattacharya
Simon P. Wilson
233
5
0
20 Aug 2014
On idiosyncratic stochasticity of financial leverage effects
On idiosyncratic stochasticity of financial leverage effects
Carles Bretó
177
18
0
19 Dec 2013
Parameter Estimation in Hidden Markov Models with Intractable
  Likelihoods Using Sequential Monte Carlo
Parameter Estimation in Hidden Markov Models with Intractable Likelihoods Using Sequential Monte Carlo
S. Yıldırım
Sumeetpal S. Singh
Thomas Dean
Ajay Jasra
291
38
0
17 Nov 2013
SSM: Inference for time series analysis with State Space Models
SSM: Inference for time series analysis with State Space Models
Joseph Dureau
S. Ballesteros
T. Bogich
AI4TS
548
21
0
22 Jul 2013
Consistency of maximum likelihood estimation for some dynamical systems
Consistency of maximum likelihood estimation for some dynamical systems
K. Mcgoff
S. Mukherjee
A. Nobel
Natesh Pillai
320
19
0
24 Jun 2013
Derivative-Free Estimation of the Score Vector and Observed Information
  Matrix with Application to State-Space Models
Derivative-Free Estimation of the Score Vector and Observed Information Matrix with Application to State-Space Models
Arnaud Doucet
Pierre E. Jacob
Sylvain Rubenthaler
412
25
0
21 Apr 2013
Propagation of initial errors on the parameters for linear and Gaussian
  state space models
Propagation of initial errors on the parameters for linear and Gaussian state space models
Salima El Kolei
158
1
0
14 Mar 2013
Statistical inference for dynamical systems: a review
Statistical inference for dynamical systems: a review
K. Mcgoff
S. Mukherjee
Natesh S. Pillai
AI4CE
347
50
0
27 Apr 2012
Particle-based likelihood inference in partially observed diffusion
  processes using generalised Poisson estimators
Particle-based likelihood inference in partially observed diffusion processes using generalised Poisson estimators
Jimmy Olsson
Jonas Strojby
DiffM
210
12
0
17 Aug 2010
Compound Markov counting processes and their applications to modeling
  infinitesimally over-dispersed systems
Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems
Carles Bretó
E. Ionides
241
44
0
28 Feb 2010
1
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