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Divide-and-Conquer with Sequential Monte Carlo

19 June 2014

Fredrik Lindsten

Alexandre Bouchard-Côté

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Papers citing "Divide-and-Conquer with Sequential Monte Carlo"

24 / 24 papers shown

Title
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm Eli Sennesh Hao Wu Tommaso Salvatori 74 0 0 11 Aug 2024
Learning and Sustaining Shared Normative Systems via Bayesian Rule Induction in Markov Games Ninell Oldenburg Zhi-Xuan Tan 79 5 0 20 Feb 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive design Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 83 2 0 11 Feb 2024
Using Autodiff to Estimate Posterior Moments, Marginals and Samples Sam Bowyer Thomas Heap Laurence Aitchison 63 1 0 26 Oct 2023
Massively Parallel Reweighted Wake-Sleep Thomas Heap Gavin Leech Laurence Aitchison BDL 58 2 0 18 May 2023
A divide and conquer sequential Monte Carlo approach to high dimensional filtering F. R. Crucinio A. M. Johansen 60 3 0 25 Nov 2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother Adrien Corenflos Nicolas Chopin Simo Särkkä 72 7 0 04 Feb 2022
The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems Juan Kuntz F. R. Crucinio A. M. Johansen 79 11 0 29 Oct 2021
Divide-and-Conquer Fusion Ryan S.Y. Chan M. Pollock A. M. Johansen Gareth O. Roberts 47 2 0 14 Oct 2021
Scalable Bayesian computation for crossed and nested hierarchical models O. Papaspiliopoulos Timothée Stumpf-Fétizon Giacomo Zanella 104 10 0 19 Mar 2021
Product-form estimators: exploiting independence to scale up Monte Carlo Juan Kuntz F. R. Crucinio A. M. Johansen 107 11 0 23 Feb 2021
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 132 68 0 23 Jul 2020
A Survey of Bayesian Statistical Approaches for Big Data Farzana Jahan Insha Ullah Kerrie Mengersen 102 14 0 08 Jun 2020
Particle filter efficiency under limited communication Deborshee Sen 43 2 0 21 Apr 2019
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 75 97 0 12 Mar 2019
Automated learning with a probabilistic programming language: Birch Lawrence M. Murray Thomas B. Schon 76 63 0 02 Oct 2018
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo Thomas B. Schon Andreas Svensson Lawrence M. Murray Fredrik Lindsten 68 41 0 07 Mar 2017
Bayesian Probabilistic Numerical Methods Jon Cockayne Chris J. Oates T. Sullivan Mark Girolami 106 166 0 13 Feb 2017
High-dimensional Filtering using Nested Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 78 23 0 29 Dec 2016
On embedded hidden Markov models and particle Markov chain Monte Carlo methods Axel Finke Arnaud Doucet A. M. Johansen 64 11 0 27 Oct 2016
Bayesian modelling and quantification of Raman spectroscopy M. Moores K. Gracie Jake Carson K. Faulds D. Graham Mark Girolami 16 11 0 25 Apr 2016
Inference Networks for Sequential Monte Carlo in Graphical Models Brooks Paige Frank Wood BDL 167 110 0 22 Feb 2016
Error Bounds for Sequential Monte Carlo Samplers for Multimodal Distributions Daniel Paulin Ajay Jasra Alexandre Hoang Thiery 101 18 0 29 Sep 2015
Theory of Parallel Particle Filters for Hidden Markov Models H. Chan Chiang-Wee Heng Ajay Jasra 67 3 0 15 Sep 2014