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Smoothing with Couplings of Conditional Particle Filters
Journal of the American Statistical Association (JASA), 2017
8 January 2017
Pierre E. Jacob
Fredrik Lindsten
Thomas B. Schon
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Papers citing
"Smoothing with Couplings of Conditional Particle Filters"
28 / 28 papers shown
Mixing time of the conditional backward sampling particle filter
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Debiasing Piecewise Deterministic Markov Process samplers using couplings
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On backward smoothing algorithms
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De-Sequentialized Monte Carlo: a parallel-in-time particle smoother
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The Coupled Rejection Sampler
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Unbiased Estimation of the Hessian for Partially Observed Diffusions
Proceedings of the Royal Society A (Proc. R. Soc. A), 2021
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Unbiased Estimation of the Gradient of the Log-Likelihood for a Class of Continuous-Time State-Space Models
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On Unbiased Score Estimation for Partially Observed Diffusions
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Ajay Jasra
238
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11 May 2021
Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo
Statistics and computing (Stat Comput), 2021
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Ajay Jasra
M. De Iorio
A. Beskos
J. Eriksson
295
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09 Mar 2021
On Unbiased Estimation for Discretized Models
J. Heng
Ajay Jasra
K. Law
Alexander Tarakanov
208
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24 Feb 2021
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state space models
Statistics and computing (Stat Comput), 2021
Jacob Vorstrup Goldman
Sumeetpal S. Singh
332
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08 Jan 2021
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Francisco J. R. Ruiz
Michalis K. Titsias
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Arnaud Doucet
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325
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05 Oct 2020
Double Happiness: Enhancing the Coupled Gains of L-lag Coupling via Control Variates
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Xiangxu Meng
351
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0
28 Aug 2020
Simple conditions for convergence of sequential Monte Carlo genealogies with applications
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Paul A. Jenkins
A. M. Johansen
Jere Koskela
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30 Jun 2020
Unbiased Filtering of a Class of Partially Observed Diffusions
Advances in Applied Probability (Adv. Appl. Probab.), 2020
Ajay Jasra
K. Law
Fangyuan Yu
299
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0
10 Feb 2020
Estimating Convergence of Markov chains with L-Lag Couplings
Neural Information Processing Systems (NeurIPS), 2019
N. Biswas
Pierre E. Jacob
Paul Vanetti
236
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0
23 May 2019
Elements of Sequential Monte Carlo
C. A. Naesseth
Fredrik Lindsten
Thomas B. Schon
261
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12 Mar 2019
Unbiased Smoothing using Particle Independent Metropolis-Hastings
Lawrence Middleton
George Deligiannidis
Arnaud Doucet
Pierre E. Jacob
209
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0
05 Feb 2019
Central Limit Theorems for Coupled Particle Filters
Ajay Jasra
Fangyuan Yu
304
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11 Oct 2018
Unbiased Markov chain Monte Carlo for intractable target distributions
Lawrence Middleton
George Deligiannidis
Arnaud Doucet
Pierre E. Jacob
290
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23 Jul 2018
Learning dynamical systems with particle stochastic approximation EM
Andreas Svensson
Fredrik Lindsten
293
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25 Jun 2018
Coupled conditional backward sampling particle filter
Anthony Lee
Sumeetpal S. Singh
M. Vihola
334
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Nesting Probabilistic Programs
Tom Rainforth
TPM
175
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16 Mar 2018
Unbiased Hamiltonian Monte Carlo with couplings
J. Heng
Pierre E. Jacob
367
65
0
01 Sep 2017
Unbiased Markov chain Monte Carlo with couplings
Pierre E. Jacob
J. O'Leary
Yves F. Atchadé
487
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11 Aug 2017
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo
Thomas B. Schon
Andreas Svensson
Lawrence M. Murray
Fredrik Lindsten
275
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07 Mar 2017
Importance sampling type estimators based on approximate marginal MCMC
M. Vihola
Jouni Helske
Jordan Franks
563
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08 Sep 2016
Pseudo-Marginal Hamiltonian Monte Carlo
Journal of machine learning research (JMLR), 2016
Johan Alenlöv
Arnaud Doucet
Fredrik Lindsten
256
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08 Jul 2016
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