A Common Derivation for Markov Chain Monte Carlo Algorithms with Tractable and Intractable Targets

7 July 2016

Papers citing "A Common Derivation for Markov Chain Monte Carlo Algorithms with Tractable and Intractable Targets"

8 / 8 papers shown

Title
Pseudo-Marginal Slice Sampling Iain Murray Matthew M. Graham 57 37 0 10 Oct 2015
Particle Metropolis-adjusted Langevin algorithms Christopher Nemeth Chris Sherlock Paul Fearnhead 54 24 0 23 Dec 2014
Particle Metropolis-Hastings using gradient and Hessian information J. Dahlin Fredrik Lindsten Thomas B. Schon 72 47 0 04 Nov 2013
On the efficiency of pseudo-marginal random walk Metropolis algorithms Chris Sherlock Alexandre Hoang Thiery Gareth O. Roberts Jeffrey S. Rosenthal 55 190 0 27 Sep 2013
Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost Christopher Nemeth Paul Fearnhead Lyudmila Mihaylova 85 45 0 04 Jun 2013
Parallel MCMC with Generalized Elliptical Slice Sampling Robert Nishihara Iain Murray Ryan P. Adams 81 81 0 28 Oct 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 152 4,275 0 18 Nov 2011
SMC^2: an efficient algorithm for sequential analysis of state-space models Nicolas Chopin Pierre E. Jacob O. Papaspiliopoulos 82 356 0 07 Jan 2011