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The iterated auxiliary particle filter

19 November 2015

Pieralberto Guarniero

Papers citing "The iterated auxiliary particle filter"

42 / 42 papers shown

Title
RNE: a plug-and-play framework for diffusion density estimation and inference-time control Jiajun He Jose Miguel Hernandez-Lobato Yuanqi Du Francisco Vargas 74 0 0 06 Jun 2025
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series Byoungwoo Park Hyungi Lee Juho Lee AI4TS 201 1 0 08 Oct 2024
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models Luhuan Wu Brian L. Trippe C. A. Naesseth David M. Blei John P. Cunningham DiffM 115 102 0 30 Jun 2023
Designing Proposal Distributions for Particle Filters using Integrated Nested Laplace Approximation A. Amri 53 1 0 05 May 2023
Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems Adrien Corenflos Simo Särkkä 72 0 0 01 Mar 2023
A divide and conquer sequential Monte Carlo approach to high dimensional filtering F. R. Crucinio A. M. Johansen 51 3 0 25 Nov 2022
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 45 11 0 26 Oct 2022
Monte Carlo twisting for particle filters Joshua J. Bon Christopher C. Drovandi Anthony Lee 18 1 0 08 Aug 2022
SIXO: Smoothing Inference with Twisted Objectives Dieterich Lawson Allan Raventós Andrew Warrington Scott W. Linderman BDL 260 15 0 13 Jun 2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother Adrien Corenflos Nicolas Chopin Simo Särkkä 68 7 0 04 Feb 2022
Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models Andras Fulop J. Heng Junye Li 61 1 0 04 Jan 2022
The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems Juan Kuntz F. R. Crucinio A. M. Johansen 73 11 0 29 Oct 2021
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality Ning Ning E. Ionides 49 13 0 20 Oct 2021
Annealed Flow Transport Monte Carlo Michael Arbel A. G. Matthews Arnaud Doucet 93 78 0 15 Feb 2021
Sequential Monte Carlo algorithms for agent-based models of disease transmission Nianqiao P. Ju J. Heng Pierre E. Jacob 19 10 0 28 Jan 2021
Optimized Auxiliary Particle Filters: adapting mixture proposals via convex optimization Nicola Branchini Victor Elvira 84 19 0 18 Nov 2020
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 129 68 0 23 Jul 2020
Conditional particle filters with diffuse initial distributions Santeri Karppinen M. Vihola 44 3 0 26 Jun 2020
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 189 55 0 23 Mar 2020
Generalized Bayesian Filtering via Sequential Monte Carlo Ayman Boustati Ömer Deniz Akyildiz Theodoros Damoulas A. M. Johansen 65 4 0 23 Feb 2020
State Space Emulation and Annealed Sequential Monte Carlo for High Dimensional Optimization Chencheng Cai Rong Chen 20 0 0 17 Nov 2019
Forecasting observables with particle filters: Any filter will do! Patrick Leung Catherine S. Forbes G. Martin Brendan P. M. McCabe AI4TS 38 0 0 20 Aug 2019
On importance-weighted autoencoders Axel Finke Alexandre Hoang Thiery 13 2 0 24 Jul 2019
Streaming Variational Monte Carlo Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 285 21 0 04 Jun 2019
Replica Conditional Sequential Monte Carlo Alexander Y. Shestopaloff Arnaud Doucet 54 3 0 13 May 2019
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 75 97 0 12 Mar 2019
Graphical model inference: Sequential Monte Carlo meets deterministic approximations Fredrik Lindsten Jouni Helske M. Vihola 85 14 0 08 Jan 2019
Optimal input potential functions in the interacting particle system method Hassane Chraïbi A. Dutfoy T. Galtier Josselin Garnier 16 7 0 26 Nov 2018
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach Alexander Lin Yingzhuo Zhang J. Heng Stephen A. Allsop K. Tye Pierre E. Jacob Demba E. Ba AI4TS 83 13 0 23 Oct 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 74 10 0 23 May 2018
Continuous-discrete smoothing of diffusions Marcin Mider Moritz Schauer Frank van der Meulen 47 30 0 11 Dec 2017
Controlled Sequential Monte Carlo J. Heng A. Bishop George Deligiannidis Arnaud Doucet 99 74 0 28 Aug 2017
Negative association, ordering and convergence of resampling methods Mathieu Gerber Nicolas Chopin N. Whiteley 75 73 0 06 Jul 2017
Sequential quasi-Monte Carlo: Introduction for Non-Experts, Dimension Reduction, Application to Partly Observed Diffusion Processes Nicolas Chopin Mathieu Gerber 52 3 0 16 Jun 2017
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 299 215 0 31 May 2017
Smoothing with Couplings of Conditional Particle Filters Pierre E. Jacob Fredrik Lindsten Thomas B. Schon 125 55 0 08 Jan 2017
Importance sampling type estimators based on approximate marginal MCMC M. Vihola Jouni Helske Jordan Franks 90 25 0 08 Sep 2016
Approximate Smoothing and Parameter Estimation in High-Dimensional State-Space Models Axel Finke Sumeetpal S. Singh 96 18 0 28 Jun 2016
Coupling of Particle Filters Pierre E. Jacob Fredrik Lindsten Thomas B. Schon 94 24 0 03 Jun 2016
Particle Smoothing for Hidden Diffusion Processes: Adaptive Path Integral Smoother H. Ruiz H. Kappen 147 37 0 01 May 2016
The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models O. Grothe T. S. Kleppe R. Liesenfeld 48 13 0 06 Jan 2016
The Correlated Pseudo-Marginal Method George Deligiannidis Arnaud Doucet M. Pitt 115 101 0 16 Nov 2015