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Particle Metropolis-Hastings using gradient and Hessian information

4 November 2013

J. Dahlin

Fredrik Lindsten

Thomas B. Schon

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Papers citing "Particle Metropolis-Hastings using gradient and Hessian information"

22 / 22 papers shown

Title
Sequential Monte Carlo with active subspaces Leonardo Ripoli Richard G. Everitt 16 0 0 08 Nov 2024
Enhanced SMC $^2$ : Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals Conor Rosato Joshua Murphy Alessandro Varsi P. Horridge Simon Maskell 96 4 0 24 Jul 2024
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters Conor Rosato Vincent Beraud P. Horridge Thomas B. Schon Simon Maskell 82 14 0 02 Nov 2021
Nonlinear input design as optimal control of a Hamiltonian system Jack Umenberger Thomas B. Schon 21 5 0 06 Mar 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
Regularized Zero-Variance Control Variates Leah F. South Chris J. Oates Antonietta Mira Christopher C. Drovandi BDL 102 19 0 13 Nov 2018
Simulation-based inference methods for partially observed Markov model via the R package is2 Bernhard Bergmair Johann Hoffelner Siegfried Silber 117 0 0 07 Nov 2018
Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals J. Dahlin A. Wills B. Ninness 39 0 0 26 Jun 2018
Constructing Metropolis-Hastings proposals using damped BFGS updates J. Dahlin A. Wills B. Ninness 58 2 0 04 Jan 2018
Particle Filters and Data Assimilation Paul Fearnhead H. Kunsch 83 82 0 13 Sep 2017
Fast approximate Bayesian inference for stable differential equation models Philip Maybank I. Bojak R. Everitt 69 9 0 02 Jun 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
A rare event approach to high dimensional Approximate Bayesian computation D. Prangle R. Everitt T. Kypraios 92 22 0 08 Nov 2016
A Common Derivation for Markov Chain Monte Carlo Algorithms with Tractable and Intractable Targets K. Tran BDL 69 2 0 07 Jul 2016
Accelerating pseudo-marginal Metropolis-Hastings by correlating auxiliary variables J. Dahlin Fredrik Lindsten J. Kronander Thomas B. Schon 86 37 0 17 Nov 2015
Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models J. Dahlin Thomas B. Schon 97 25 0 05 Nov 2015
Sequential Monte Carlo Methods for System Identification Thomas B. Schon Fredrik Lindsten J. Dahlin Johan Waagberg C. A. Naesseth Andreas Svensson L. Dai 111 79 0 20 Mar 2015
Quasi-Newton particle Metropolis-Hastings J. Dahlin Fredrik Lindsten Thomas B. Schon 155 9 0 12 Feb 2015
On Particle Methods for Parameter Estimation in State-Space Models N. Kantas Arnaud Doucet Sumeetpal S. Singh J. Maciejowski Nicolas Chopin 119 435 0 30 Dec 2014
Particle Metropolis-adjusted Langevin algorithms Christopher Nemeth Chris Sherlock Paul Fearnhead 124 24 0 23 Dec 2014
Augmentation Schemes for Particle MCMC Paul Fearnhead Loukia Meligkotsidou 90 19 0 29 Aug 2014
Data augmentation for models based on rejection sampling Vinayak A. Rao Lizhen Lin David B. Dunson BDL 124 23 0 25 Jun 2014