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On Particle Methods for Parameter Estimation in State-Space Models

30 December 2014

Papers citing "On Particle Methods for Parameter Estimation in State-Space Models"

50 / 118 papers shown

Title
Optimized Auxiliary Particle Filters: adapting mixture proposals via convex optimization Nicola Branchini Victor Elvira 84 19 0 18 Nov 2020
End-To-End Semi-supervised Learning for Differentiable Particle Filters Hao Wen Xiongjie Chen Georgios Papagiannis Conghui Hu Yunpeng Li 65 17 0 11 Nov 2020
Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation Louis Sharrock N. Kantas 20 10 0 18 Sep 2020
Approximating Posterior Predictive Distributions by Averaging Output From Many Particle Filters Taylor R. Brown 16 2 0 27 Jun 2020
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM Kunal Menda J. Becdelievre Jayesh K. Gupta I. Kroo Mykel J. Kochenderfer Zachary Manchester 23 7 0 20 Jun 2020
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes Manuel Haussmann S. Gerwinn Andreas Look Barbara Rakitsch M. Kandemir 86 16 0 17 Jun 2020
An algorithm for non-parametric estimation in state-space models T. Chau P. Ailliot V. Monbet 13 10 0 16 Jun 2020
Real-Time Model Calibration with Deep Reinforcement Learning Yuan Tian M. A. Chao Chetan S. Kulkarni K. Goebel Olga Fink AI4CE 65 49 0 07 Jun 2020
Coping With Simulators That Don't Always Return Andrew Warrington Saeid Naderiparizi Frank Wood 48 4 0 28 Mar 2020
Online Smoothing for Diffusion Processes Observed with Noise S. Yonekura A. Beskos 38 9 0 27 Mar 2020
Generalized Bayesian Filtering via Sequential Monte Carlo Ayman Boustati Ömer Deniz Akyildiz Theodoros Damoulas A. M. Johansen 65 4 0 23 Feb 2020
PF: A C++ Library for Fast Particle Filtering Taylor R. Brown 33 0 0 28 Jan 2020
Relational State-Space Model for Stochastic Multi-Object Systems Fan Yang Ling Chen Fan Zhou Yusong Gao Wei Cao 75 8 0 13 Jan 2020
Model uncertainty estimation using the expectation maximization algorithm and a particle flow filter M. M. Lucini P. Leeuwen M. Pulido 66 4 0 04 Nov 2019
Combined parameter and state inference with automatically calibrated ABC Anthony Ebert Pierre Pudlo Kerrie Mengersen P. Wu Christopher C. Drovandi 45 1 0 31 Oct 2019
Probabilistic sequential matrix factorization Ömer Deniz Akyildiz Gerrit J. J. van den Burg Theodoros Damoulas M. Steel 42 2 0 09 Oct 2019
Stochastic quasi-Newton with line-search regularization A. Wills Thomas B. Schon ODL 68 21 0 03 Sep 2019
The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging Andrew Warrington A. Spencer Frank Wood 31 2 0 24 Jul 2019
A Kalman particle filter for online parameter estimation with applications to affine models Jian He Asma Khedher Peter Spreij 43 6 0 21 May 2019
Unbiased Smoothing using Particle Independent Metropolis-Hastings Lawrence Middleton George Deligiannidis Arnaud Doucet Pierre E. Jacob 69 22 0 05 Feb 2019
Stochastic Gradient MCMC for Nonlinear State Space Models Christopher Aicher Srshti Putcha Christopher Nemeth Paul Fearnhead E. Fox BDL 64 8 0 29 Jan 2019
Bias of Particle Approximations to Optimal Filter Derivative V. Tadic Arnaud Doucet 34 1 0 25 Jun 2018
Accelerating delayed-acceptance Markov chain Monte Carlo algorithms Samuel Wiqvist Umberto Picchini J. Forman Kresten Lindorff-Larsen Wouter Boomsma 38 8 0 15 Jun 2018
Parameter Learning and Change Detection Using a Particle Filter With Accelerated Adaptation Karol Gellert Erik Schlögl 40 3 0 14 Jun 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 74 10 0 23 May 2018
Improved and Scalable Online Learning of Spatial Concepts and Language Models with Mapping Akira Taniguchi Y. Hagiwara T. Taniguchi T. Inamura 64 27 0 09 Mar 2018
Stochastic quasi-Newton with adaptive step lengths for large-scale problems A. Wills Thomas B. Schon 61 9 0 12 Feb 2018
Improving the particle filter in high dimensions using conjugate artificial process noise A. Wigren Lawrence M. Murray Fredrik Lindsten 23 9 0 22 Jan 2018
Particle-based, online estimation of tangent filters with application to parameter estimation in nonlinear state-space models Jimmy Olsson Johan Westerborn Alenlöv 64 10 0 22 Dec 2017
Particle Filters and Data Assimilation Paul Fearnhead H. Kunsch 83 82 0 13 Sep 2017
A probabilistic scheme for joint parameter estimation and state prediction in complex dynamical systems Sara Pérez-Vieites I. P. Mariño Joaquín Míguez 76 16 0 11 Aug 2017
Latent Parameter Estimation in Fusion Networks Using Separable Likelihoods Murat Üney B. Mulgrew Daniel E. Clark FedML 28 14 0 02 Aug 2017
Identification of multi-object dynamical systems: consistency and Fisher information J. Houssineau Sumeetpal S. Singh Ajay Jasra 52 4 0 14 Jul 2017
Fast approximate Bayesian inference for stable differential equation models Philip Maybank I. Bojak R. Everitt 71 9 0 02 Jun 2017
A critical analysis of resampling strategies for the regularized particle filter Pierre Carmier Olexiy O. Kyrgyzov P. Cournède 18 2 0 11 May 2017
Advanced Multilevel Monte Carlo Methods Ajay Jasra K. Law C. Suciu 56 16 0 24 Apr 2017
On the construction of probabilistic Newton-type algorithms A. Wills Thomas B. Schon 58 13 0 05 Apr 2017
Sequential Monte Carlo Methods in the nimble R Package Nick Michaud P. de Valpine Daniel Turek C. Paciorek D. Nguyen 73 6 0 17 Mar 2017
Inference via low-dimensional couplings Alessio Spantini Daniele Bigoni Youssef Marzouk 134 119 0 17 Mar 2017
Particle Value Functions Chris J. Maddison Dieterich Lawson George Tucker N. Heess Arnaud Doucet A. Mnih Yee Whye Teh 83 15 0 16 Mar 2017
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo Thomas B. Schon Andreas Svensson Lawrence M. Murray Fredrik Lindsten 56 41 0 07 Mar 2017
Analysis of a nonlinear importance sampling scheme for Bayesian parameter estimation in state-space models Joaquín Míguez I. P. Mariño M. A. Vázquez 35 11 0 10 Feb 2017
Learning of state-space models with highly informative observations: a tempered Sequential Monte Carlo solution Andreas Svensson Thomas B. Schon Fredrik Lindsten 58 17 0 06 Feb 2017
Smoothing with Couplings of Conditional Particle Filters Pierre E. Jacob Fredrik Lindsten Thomas B. Schon 125 55 0 08 Jan 2017
On embedded hidden Markov models and particle Markov chain Monte Carlo methods Axel Finke Arnaud Doucet A. M. Johansen 56 11 0 27 Oct 2016
Likelihood-free stochastic approximation EM for inference in complex models Umberto Picchini TPM 34 5 0 12 Sep 2016
Approximate Smoothing and Parameter Estimation in High-Dimensional State-Space Models Axel Finke Sumeetpal S. Singh 96 18 0 28 Jun 2016
Coupling of Particle Filters Pierre E. Jacob Fredrik Lindsten Thomas B. Schon 94 24 0 03 Jun 2016
On Coupling Particle Filter Trajectories Deborshee Sen Alexandre Hoang Thiery Ajay Jasra 99 21 0 03 Jun 2016
On the two-filter approximations of marginal smoothing distributions in general state space models T. Nguyen Sylvain Le Corff Eric Moulines 48 8 0 27 May 2016