Optimized Auxiliary Particle Filters: adapting mixture proposals via convex optimization

18 November 2020

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

6 / 6 papers shown

Title
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks Benjamin Cox Santiago Segarra Victor Elvira 78 0 0 23 Nov 2024
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models Benjamin Cox Victor Elvira 41 10 0 20 Jun 2023
Designing Proposal Distributions for Particle Filters using Integrated Nested Laplace Approximation A. Amri 29 1 0 05 May 2023
Properties of Marginal Sequential Monte Carlo Methods F. R. Crucinio A. M. Johansen 26 2 0 06 Mar 2023
Differentiable Bootstrap Particle Filters for Regime-Switching Models Wenhan Li Xiongjie Chen Wenwu Wang Victor Elvira Yunpeng Li 43 6 0 20 Feb 2023
Unsupervised Learning of Sampling Distributions for Particle Filters Fernando Gama Nicolas Zilberstein Martín Sevilla Richard Baraniuk Santiago Segarra 40 9 0 02 Feb 2023