On Particle Methods for Parameter Estimation in State-Space Models

30 December 2014

Papers citing "On Particle Methods for Parameter Estimation in State-Space Models"

37 / 37 papers shown

Title
Learning to be Smooth: An End-to-End Differentiable Particle Smoother Ali Younis Erik B. Sudderth AI4TS 38 0 0 14 Feb 2025
Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation Yang Cao Zhao-quan Song Chiwun Yang VGen 44 2 0 01 Feb 2025
Sparse Graphical Linear Dynamical Systems Émilie Chouzenoux Victor Elvira 25 7 0 06 Jul 2023
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models Benjamin Cox Victor Elvira 36 10 0 20 Jun 2023
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics Matthew Dowling Yuan Zhao Il Memming Park BDL OffRL 21 6 0 18 May 2023
Designing Proposal Distributions for Particle Filters using Integrated Nested Laplace Approximation A. Amri 19 1 0 05 May 2023
Differentiable Bootstrap Particle Filters for Regime-Switching Models Wenhan Li Xiongjie Chen Wenwu Wang Victor Elvira Yunpeng Li 30 6 0 20 Feb 2023
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving Angad Singh Omar Makhlouf Maximilian Igl Joao Messias Arnaud Doucet Shimon Whiteson 42 2 0 14 Dec 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 11 10 0 26 Oct 2022
Online Probabilistic Model Identification using Adaptive Recursive MCMC Pedram Agand Mo Chen H. Taghirad 35 4 0 23 Oct 2022
Can a latent Hawkes process be used for epidemiological modelling? Stamatina Lamprinakou Axel Gandy E. McCoy 14 1 0 15 Aug 2022
Inference of Regulatory Networks Through Temporally Sparse Data Mohammad Alali Mahdi Imani 17 17 0 21 Jul 2022
When Artificial Parameter Evolution Gets Real: Particle Filtering for Time-Varying Parameter Estimation in Deterministic Dynamical Systems Andrea Arnold 13 6 0 31 Mar 2022
Conditional Measurement Density Estimation in Sequential Monte Carlo via Normalizing Flow Xiongjie Chen Yunpeng Li 13 6 0 16 Mar 2022
The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems Juan Kuntz F. R. Crucinio A. M. Johansen 19 11 0 29 Oct 2021
Online Variational Filtering and Parameter Learning Andrew Campbell Yuyang Shi Tom Rainforth Arnaud Doucet BDL 25 21 0 26 Oct 2021
Differentiable Particle Filters through Conditional Normalizing Flow Xiongjie Chen Hao Wen Yunpeng Li 21 20 0 01 Jul 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan Willem van de Meent BDL 18 20 0 21 Jun 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 39 66 0 15 Feb 2021
End-To-End Semi-supervised Learning for Differentiable Particle Filters Hao Wen Xiongjie Chen Georgios Papagiannis Conghui Hu Yunpeng Li 22 17 0 11 Nov 2020
Generalized Bayesian Filtering via Sequential Monte Carlo Ayman Boustati Ömer Deniz Akyildiz Theodoros Damoulas A. M. Johansen 14 4 0 23 Feb 2020
Stochastic quasi-Newton with line-search regularization A. Wills Thomas B. Schon ODL 11 21 0 03 Sep 2019
Parameter Learning and Change Detection Using a Particle Filter With Accelerated Adaptation Karol Gellert Erik Schlögl 11 3 0 14 Jun 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 13 10 0 23 May 2018
Particle-based, online estimation of tangent filters with application to parameter estimation in nonlinear state-space models Jimmy Olsson Johan Westerborn Alenlöv 16 10 0 22 Dec 2017
Sequential Monte Carlo Methods in the nimble R Package Nick Michaud P. de Valpine Daniel Turek C. Paciorek D. Nguyen 31 6 0 17 Mar 2017
Inference via low-dimensional couplings Alessio Spantini Daniele Bigoni Youssef Marzouk 27 119 0 17 Mar 2017
On embedded hidden Markov models and particle Markov chain Monte Carlo methods Axel Finke Arnaud Doucet A. M. Johansen 11 11 0 27 Oct 2016
Approximate Smoothing and Parameter Estimation in High-Dimensional State-Space Models Axel Finke Sumeetpal S. Singh 37 16 0 28 Jun 2016
Coupling of Particle Filters Pierre E. Jacob Fredrik Lindsten Thomas B. Schon 22 24 0 03 Jun 2016
On Coupling Particle Filter Trajectories Deborshee Sen Alexandre Hoang Thiery Ajay Jasra 23 21 0 03 Jun 2016
Uniform convergence over time of a nested particle filtering scheme for recursive parameter estimation in state--space Markov models Dan Crisan Joaquín Míguez 11 12 0 30 Mar 2016
Towards Practical Bayesian Parameter and State Estimation Yusuf Erol Yi Wu Lei Li Stuart J. Russell 24 0 0 29 Mar 2016
A flexible state space model for learning nonlinear dynamical systems Andreas Svensson Thomas B. Schon 14 104 0 17 Mar 2016
Sequential Empirical Bayes method for filtering dynamic spatiotemporal processes E. Evangelou Vasileios Maroulas 25 7 0 08 Jun 2015
Biased Online Parameter Inference for State-Space Models Yan Zhou Ajay Jasra 36 9 0 01 Mar 2015
On Particle Learning Nicolas Chopin A. Iacobucci Jean-Michel Marin Kerrie Mengersen Christian P. Robert Robin J. Ryder Christian Schafer 65 28 0 03 Jun 2010