Optimized Auxiliary Particle Filters: adapting mixture proposals via
convex optimization

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Optimized Auxiliary Particle Filters: adapting mixture proposals via convex optimization

18 November 2020

Nicola Branchini

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Papers citing "Optimized Auxiliary Particle Filters: adapting mixture proposals via convex optimization"

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Title
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks Benjamin Cox Santiago Segarra Victor Elvira 154 0 0 23 Nov 2024
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models Benjamin Cox Victor Elvira 64 10 0 20 Jun 2023
Designing Proposal Distributions for Particle Filters using Integrated Nested Laplace Approximation A. Amri 53 1 0 05 May 2023
Properties of Marginal Sequential Monte Carlo Methods F. R. Crucinio A. M. Johansen 49 3 0 06 Mar 2023
Differentiable Bootstrap Particle Filters for Regime-Switching Models Wenhan Li Xiongjie Chen Wenwu Wang Victor Elvira Yunpeng Li 74 6 0 20 Feb 2023
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference Xiongjie Chen Yunpeng Li 78 15 0 19 Feb 2023
Unsupervised Learning of Sampling Distributions for Particle Filters Fernando Gama Nicolas Zilberstein Martín Sevilla Richard Baraniuk Santiago Segarra 91 10 0 02 Feb 2023
The Lifebelt Particle Filter for robust estimation from low-valued count data Alice Corbella T. McKinley Paul J. Birrell A. Presanis S. Spencer Gareth O. Roberts Daniela De Angelis 40 1 0 08 Dec 2022
Graphical Inference in Linear-Gaussian State-Space Models Victor Elvira Émilie Chouzenoux 30 16 0 20 Sep 2022
Variational Marginal Particle Filters Jinlin Lai Justin Domke Daniel Sheldon 89 9 0 30 Sep 2021