Quantifying the accuracy of approximate diffusions and Markov chains

20 May 2016

Papers citing "Quantifying the accuracy of approximate diffusions and Markov chains"

8 / 8 papers shown

Title
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 11 135 0 16 Jul 2019
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 9 15 0 26 Jun 2018
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 11 31 0 26 Sep 2017
Informed Sub-Sampling MCMC: Approximate Bayesian Inference for Large Datasets Florian Maire Nial Friel Pierre Alquier 26 14 0 26 Jun 2017
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 53 232 0 11 Jul 2016
Piecewise deterministic Markov process - recent results Romain Azais Jean-Baptiste Bardet A. Genadot Nathalie Krell P. Zitt 43 66 0 24 Sep 2013
Efficient Solution to the 3D Problem of Automatic Wall Paintings Reassembly A. S. Keys Dimitris Arabadjis C. Iacovella Panayiotis Rousopoulos S. Glotzer Michail Panagopoulos Lena Papazoglou-Manioudaki 3DV 41 134 0 10 Oct 2012
MCMC using Hamiltonian dynamics Radford M. Neal 132 3,263 0 09 Jun 2012