ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 0803.0054
  4. Cited By
Adaptive methods for sequential importance sampling with application to
  state space models
v1v2 (latest)

Adaptive methods for sequential importance sampling with application to state space models

European Signal Processing Conference (EUSIPCO), 2008
1 March 2008
Julien Cornebise
Eric Moulines
Jimmy Olsson
ArXiv (abs)PDFHTML

Papers citing "Adaptive methods for sequential importance sampling with application to state space models"

31 / 31 papers shown
Global convergence of optimized adaptive importance samplers
Global convergence of optimized adaptive importance samplersFoundations of Data Science (FODS), 2022
Ömer Deniz Akyildiz
331
9
0
02 Jan 2022
An invitation to sequential Monte Carlo samplers
An invitation to sequential Monte Carlo samplers
Chenguang Dai
J. Heng
Pierre E. Jacob
N. Whiteley
475
85
0
23 Jul 2020
Targeted free energy estimation via learned mappings
Targeted free energy estimation via learned mappingsJournal of Chemical Physics (JCP), 2020
Peter Wirnsberger
A. J. Ballard
George Papamakarios
Stuart Abercrombie
S. Racanière
Alexander Pritzel
Danilo Jimenez Rezende
Charles Blundell
268
110
0
12 Feb 2020
On importance-weighted autoencoders
On importance-weighted autoencoders
Axel Finke
Alexandre Hoang Thiery
269
2
0
24 Jul 2019
Generalizing the Balance Heuristic Estimator in Multiple Importance
  Sampling
Generalizing the Balance Heuristic Estimator in Multiple Importance Sampling
M. Sbert
Victor Elvira
337
18
0
28 Mar 2019
Elements of Sequential Monte Carlo
Elements of Sequential Monte Carlo
C. A. Naesseth
Fredrik Lindsten
Thomas B. Schon
261
112
0
12 Mar 2019
An Introduction to Probabilistic Programming
An Introduction to Probabilistic Programming
Jan-Willem van de Meent
Brooks Paige
Hongseok Yang
Frank Wood
GP
379
220
0
27 Sep 2018
Inference Trees: Adaptive Inference with Exploration
Inference Trees: Adaptive Inference with Exploration
Tom Rainforth
Yuanshuo Zhou
Xiaoyu Lu
Yee Whye Teh
Frank Wood
Hongseok Yang
Jan-Willem van de Meent
TPM
198
12
0
25 Jun 2018
Scalable Bayesian Learning for State Space Models using Variational
  Inference with SMC Samplers
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers
Marcel Hirt
P. Dellaportas
BDL
287
11
0
23 May 2018
Semi-independent resampling for particle filtering
Semi-independent resampling for particle filtering
Roland Lamberti
Y. Petetin
F. Desbouvries
F. Septier
90
9
0
15 Oct 2017
Negative association, ordering and convergence of resampling methods
Negative association, ordering and convergence of resampling methods
Mathieu Gerber
Nicolas Chopin
N. Whiteley
297
76
0
06 Jul 2017
Particle Filtering with Invertible Particle Flow
Particle Filtering with Invertible Particle Flow
Yunpeng Li
Mark Coates
418
64
0
29 Jul 2016
Independent Resampling Sequential Monte Carlo Algorithms
Independent Resampling Sequential Monte Carlo Algorithms
Roland Lamberti
Y. Petetin
F. Desbouvries
F. Septier
148
16
0
19 Jul 2016
Particle Smoothing for Hidden Diffusion Processes: Adaptive Path
  Integral Smoother
Particle Smoothing for Hidden Diffusion Processes: Adaptive Path Integral Smoother
H. Ruiz
H. Kappen
469
37
0
01 May 2016
Inference Networks for Sequential Monte Carlo in Graphical Models
Inference Networks for Sequential Monte Carlo in Graphical Models
Brooks Paige
Frank Wood
BDL
444
115
0
22 Feb 2016
Bayesian subset simulation
Bayesian subset simulation
Julien Bect
Ling Li
E. Vázquez
350
74
0
11 Jan 2016
Adapting the Number of Particles in Sequential Monte Carlo Methods
  through an Online Scheme for Convergence Assessment
Adapting the Number of Particles in Sequential Monte Carlo Methods through an Online Scheme for Convergence Assessment
Victor Elvira
Joaquín Míguez
Petar M. Djurić
248
75
0
16 Sep 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
278
74
0
24 May 2015
A proof of uniform convergence over time for a distributed particle
  filter
A proof of uniform convergence over time for a distributed particle filterSignal Processing (Signal Process.), 2015
Joaquín Míguez
M. A. Vázquez
331
23
0
05 Apr 2015
Sequential Monte Carlo as Approximate Sampling: bounds, adaptive
  resampling via $\infty$-ESS, and an application to Particle Gibbs
Sequential Monte Carlo as Approximate Sampling: bounds, adaptive resampling via ∞\infty∞-ESS, and an application to Particle Gibbs
Jonathan H. Huggins
Daniel M. Roy
291
20
0
03 Mar 2015
Fighting Sample Degeneracy and Impoverishment in Particle Filters: A
  Review of Intelligent Approaches
Fighting Sample Degeneracy and Impoverishment in Particle Filters: A Review of Intelligent ApproachesExpert systems with applications (ESWA), 2013
Tiancheng Li
Shudong Sun
T. Sattar
J. Corchado
445
245
0
12 Aug 2013
On-line Bayesian parameter estimation in general non-linear state-space
  models: A tutorial and new results
On-line Bayesian parameter estimation in general non-linear state-space models: A tutorial and new results
Aditya Tulsyan
Biao Huang
R. Bhushan Gopaluni
J. Forbes
134
6
0
12 Jul 2013
Adapting sample size in particle filters through KLD-resampling
Adapting sample size in particle filters through KLD-resampling
Tiancheng Li
Shudong Sun
T. Sattar
138
77
0
13 Jun 2013
On adaptive resampling strategies for sequential Monte Carlo methods
On adaptive resampling strategies for sequential Monte Carlo methods
P. Del Moral
Arnaud Doucet
Ajay Jasra
196
187
0
02 Mar 2012
Adaptive sequential Monte Carlo by means of mixture of experts
Adaptive sequential Monte Carlo by means of mixture of experts
Julien Cornebise
Eric Moulines
Jimmy Olsson
284
11
0
14 Aug 2011
On optimality of kernels for approximate Bayesian computation using
  sequential Monte Carlo
On optimality of kernels for approximate Bayesian computation using sequential Monte CarloStatistical Applications in Genetics and Molecular Biology (SAGMB), 2011
Sarah Filippi
Chris P. Barnes
Julien Cornebise
M. Stumpf
663
138
0
30 Jun 2011
Ecological non-linear state space model selection via adaptive particle
  Markov chain Monte Carlo (AdPMCMC)
Ecological non-linear state space model selection via adaptive particle Markov chain Monte Carlo (AdPMCMC)
G. Peters
G. Hosack
K. Hayes
340
47
0
13 May 2010
An Adaptive Sequential Monte Carlo Sampler
An Adaptive Sequential Monte Carlo Sampler
Paul Fearnhead
Benjamin M. Taylor
280
85
0
07 May 2010
Comments on "Particle Markov Chain Monte Carlo" by C. Andrieu, A. Doucet
  and R. Hollenstein
Comments on "Particle Markov Chain Monte Carlo" by C. Andrieu, A. Doucet and R. Hollenstein
Julien Cornebise
G. Peters
251
1
0
19 Nov 2009
On the Forward Filtering Backward Smoothing particle approximations of
  the smoothing distribution in general state spaces models
On the Forward Filtering Backward Smoothing particle approximations of the smoothing distribution in general state spaces models
Randal Douc
Aurélien Garivier
Eric Moulines
Jimmy Olsson
302
22
0
02 Apr 2009
On sequential Monte Carlo, partial rejection control and approximate
  Bayesian computation
On sequential Monte Carlo, partial rejection control and approximate Bayesian computationStatistics and computing (Stat. Comput.), 2008
G. Peters
Yanan Fan
Scott A. Sisson
360
74
0
26 Aug 2008
1
Page 1 of 1