Can local particle filters beat the curse of dimensionality?

28 January 2013

Papers citing "Can local particle filters beat the curse of dimensionality?"

50 / 75 papers shown

Title
Localized Diffusion Models for High Dimensional Distributions Generation Georg Gottwald Shuigen Liu Youssef Marzouk Sebastian Reich X. Tong DiffM 35 0 0 07 May 2025
A convergent scheme for the Bayesian filtering problem based on the Fokker--Planck equation and deep splitting Kasper Bågmark Adam Andersson S. Larsson Filip Rydin 79 0 0 20 Jan 2025
Accuracy of the Ensemble Kalman Filter in the Near-Linear Setting Edoardo Calvello Pierre Monmarché Andrew M. Stuart U. Vaes 34 3 0 15 Sep 2024
Learning Flock: Enhancing Sets of Particles for Multi~Sub-State Particle Filtering with Neural Augmentation Itai Nuri Nir Shlezinger 26 0 0 21 Aug 2024
Ensemble Transport Filter via Optimized Maximum Mean Discrepancy Dengfei Zeng Lijian Jiang OT 19 1 0 16 Jul 2024
PASOA- PArticle baSed Bayesian Optimal Adaptive design Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 13 1 0 11 Feb 2024
Nonlinear Filtering with Brenier Optimal Transport Maps Mohammad Al-Jarrah Niyizhen Jin Bamdad Hosseini Amirhossein Taghvaei 29 2 0 21 Oct 2023
A State-Space Perspective on Modelling and Inference for Online Skill Rating Samuel Duffield Samuel Power Lorenzo Rimella 15 6 0 04 Aug 2023
Principal Feature Detection via $Φ$ -Sobolev Inequalities Matthew T.C. Li Youssef Marzouk O. Zahm 26 8 0 10 May 2023
A divide and conquer sequential Monte Carlo approach to high dimensional filtering F. R. Crucinio A. M. Johansen 21 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 15 10 0 26 Oct 2022
Polynomial time guarantees for sampling based posterior inference in high-dimensional generalised linear models R. Altmeyer 28 4 0 28 Aug 2022
Adaptive online variance estimation in particle filters: the ALVar estimator Alessandro Mastrototaro Jimmy Olsson 15 2 0 19 Jul 2022
Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces Dawei Chen Samuel Yang-Zhao John Lloyd K. S. Ng AI4TS 4 1 0 05 Jun 2022
Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods M. Whitehouse N. Whiteley Lorenzo Rimella 13 12 0 26 May 2022
An Optimal Transport Formulation of Bayes' Law for Nonlinear Filtering Algorithms Amirhossein Taghvaei Bamdad Hosseini OT 32 17 0 22 Mar 2022
State space partitioning based on constrained spectral clustering for block particle filtering Rui Min C. Garnier Françcois Septier John Klein 19 8 0 07 Mar 2022
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality Ning Ning E. Ionides 14 13 0 20 Oct 2021
A Lagged Particle Filter for Stable Filtering of certain High-Dimensional State-Space Models Hamza Ruzayqat A. Er-Raiy A. Beskos Dan Crisan Ajay Jasra N. Kantas 24 9 0 02 Oct 2021
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning Carlo Alfano Patrick Rebeschini 34 5 0 23 Sep 2021
Conditional sequential Monte Carlo in high dimensions Axel Finke Alexandre Hoang Thiery 8 6 0 23 Aug 2021
A comparison of nonlinear extensions to the ensemble Kalman filter: Gaussian Anamorphosis and Two-Step Ensemble Filters Ian G. Grooms 13 10 0 15 Jul 2021
Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models Enric Boix-Adserà Guy Bresler Frederic Koehler TPM 20 10 0 07 Jun 2021
On log-concave approximations of high-dimensional posterior measures and stability properties in non-linear inverse problems Jan Bohr Richard Nickl 10 17 0 17 May 2021
Multilevel Bootstrap Particle Filter K. Heine D. Burrows 6 0 0 16 Apr 2021
Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state space models Jacob Vorstrup Goldman Sumeetpal S. Singh 16 4 0 08 Jan 2021
A tutorial on spatiotemporal partially observed Markov process models via the R package spatPomp Kidus Asfaw Joonha Park Aaron M. King E. Ionides 22 3 0 04 Jan 2021
Deep FPF: Gain function approximation in high-dimensional setting S. Y. Olmez Amirhossein Taghvaei P. Mehta 16 9 0 02 Oct 2020
Bayesian Update with Importance Sampling: Required Sample Size D. Sanz-Alonso Zijian Wang 11 6 0 22 Sep 2020
On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms Richard Nickl Sven Wang 13 39 0 11 Sep 2020
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 50 65 0 23 Jul 2020
On the Mathematical Theory of Ensemble (Linear-Gaussian) Kalman-Bucy Filtering A. Bishop P. Del Moral 29 26 0 16 Jun 2020
An Optimal Transport Formulation of the Ensemble Kalman Filter Amirhossein Taghvaei P. Mehta 32 22 0 05 Oct 2019
Simulating Crowds in Real Time with Agent-Based Modelling and a Particle Filter N. Malleson K. Minors L. Kieu Jonathan A. Ward Andrew A. West A. Heppenstall AI4CE 23 31 0 20 Sep 2019
Adaptive particle-based approximations of the Gibbs posterior for inverse problems Z. Zou S. Mukherjee Harbir Antil W. Aquino 15 6 0 02 Jul 2019
A scalable optimal-transport based local particle filter Matthew M. Graham Alexandre Hoang Thiery OT 11 3 0 03 Jun 2019
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 16 95 0 12 Mar 2019
Exploiting locality in high-dimensional factorial hidden Markov models Lorenzo Rimella N. Whiteley 11 6 0 05 Feb 2019
A High-Dimensional Particle Filter Algorithm J. Quinn 11 3 0 29 Jan 2019
Predictive Learning on Hidden Tree-Structured Ising Models Konstantinos E. Nikolakakis Dionysios S. Kalogerias Anand D. Sarwate 18 12 0 11 Dec 2018
Improving the particle filter in high dimensions using conjugate artificial process noise A. Wigren Lawrence M. Murray Fredrik Lindsten 19 9 0 22 Jan 2018
Efficient Localized Inference for Large Graphical Models Jinglin Chen Jian-wei Peng Qiang Liu 18 0 0 28 Oct 2017
$Multilevel Sequential${}^2$ Monte Carlo for Bayesian Inverse Problems$ Multilevel Sequential ${}^2$ Monte Carlo for Bayesian Inverse Problems J. Latz I. Papaioannou E. Ullmann 17 41 0 27 Sep 2017
Particle Filters and Data Assimilation Paul Fearnhead H. Kunsch 6 81 0 13 Sep 2017
Nudging the particle filter Ömer Deniz Akyıldız Joaquín Míguez 29 26 0 25 Aug 2017
Dimension-free Wasserstein contraction of nonlinear filters N. Whiteley 11 4 0 04 Aug 2017
Performance analysis of local ensemble Kalman filter Xin T. Tong 44 22 0 25 May 2017
Advanced Multilevel Monte Carlo Methods Ajay Jasra K. Law C. Suciu 22 14 0 24 Apr 2017
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo Thomas B. Schon Andreas Svensson Lawrence M. Murray Fredrik Lindsten 11 41 0 07 Mar 2017
High-dimensional Filtering using Nested Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 23 22 0 29 Dec 2016