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Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals

Published:2018-01 Issue:2 Volume:6 Page:762-786
ISSN:2166-2525
Container-title:SIAM/ASA Journal on Uncertainty Quantification
language:en
Short-container-title:SIAM/ASA J. Uncertainty Quantification

Author:

Beskos Alexandros,Jasra Ajay,Law Kody,Marzouk Youssef,Zhou Yan

Funder

Oak Ridge National Laboratory

Leverhulme Trust

Ministry of Education - Singapore

U.S. Department of Energy

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Discrete Mathematics and Combinatorics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://epubs.siam.org/doi/pdf/10.1137/17M1120993

Reference25 articles.

1. On the stability of sequential Monte Carlo methods in high dimensions

2. Sequential Monte Carlo methods for Bayesian elliptic inverse problems

3. Geometric MCMC for infinite-dimensional inverse problems

4. Multilevel sequential Monte Carlo samplers

5. Convergence analysis of multilevel Monte Carlo variance estimators and application for random obstacle problems

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1. Multilevel dimension-independent likelihood-informed MCMC for large-scale inverse problems;Inverse Problems;2024-02-05

2. A randomized multi-index sequential Monte Carlo method;Statistics and Computing;2023-07-04

3. On Unbiased Estimation for Discretized Models;SIAM/ASA Journal on Uncertainty Quantification;2023-05-26

4. Multi-index Sequential Monte Carlo Ratio Estimators for Bayesian Inverse problems;Foundations of Computational Mathematics;2023-05-08

5. Bayesian updating and marginal likelihood estimation by cross entropy based importance sampling;Journal of Computational Physics;2023-01

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