The Mean-Field Ensemble Kalman Filter: Near-Gaussian Setting

Authors

José A. Carrillo (ORCID: https://orcid.org/0000-0001-8819-4660)
Urbain Vaes (ORCID: https://orcid.org/0000-0002-7629-7184)
Franca Hoffmann (ORCID: https://orcid.org/0000-0002-1182-5521)
A. M. Stuart

Institutions

California Institute of Technology (US)
École nationale des ponts et chaussées (FR)
University of Oxford (GB)
CERMICS (FR)

Publication Details

Journal: SIAM Journal on Numerical Analysis
Published: 2024-11-15
DOI: https://doi.org/10.1137/24m1628207
Citations: 4
Primary Topic: Target Tracking and Data Fusion in Sensor Networks
Type: article
Field-Weighted Citation Impact: 1.39

Funders

National Science Foundation
U.S. Department of Defense
California Institute of Technology
Deutsche Forschungsgemeinschaft
Agence Nationale de la Recherche
Engineering and Physical Sciences Research Council
Office of Naval Research
H2020 European Research Council

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article

The Mean-Field Ensemble Kalman Filter: Near-Gaussian Setting

José A. Carrillo, Urbain Vaes, Franca Hoffmann, A. M. Stuart

Nov 15, 2024

4 citations

SIAM Journal on Numerical Analysis

Target Tracking and Data Fusion in Sensor Networks

1.39

article

The Mean-Field Ensemble Kalman Filter: Near-Gaussian Setting

José A. Carrillo, Urbain Vaes, Franca Hoffmann, A. M. Stuart

November 15, 2024article en

4 citations

Abstract

No abstract available for this paper.

SIAM Journal on Numerical AnalysisVol. 62(6)

California Institute of Technology (US), École nationale des ponts et chaussées (FR), University of Oxford (GB), CERMICS (FR)

National Science Foundation, U.S. Department of Defense, California Institute of Technology, Deutsche Forschungsgemeinschaft, Agence Nationale de la Recherche, Engineering and Physical Sciences Research Council, Office of Naval Research, H2020 European Research Council

Openalex Percentile: Top 15%

Target Tracking and Data Fusion in Sensor Networks

1.39

DOI Source OpenAlex

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