Data Assimilation: From Mathematical and Statistical Foundations to Applications

Data assimilation, where predictions from a dynamical system are updated sequentially based on new and incomplete observations, is increasingly finding applications in many areas of science and technology. This workshop brought together a collection of scientists from dynamical systems, statistics, machine learning, applied probability, uncertainty quantification, and mathematical modelling, as well as practitioners in the field.

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Publication Details

Journal
Oberwolfach Reports
Published
2025-08-29
DOI
https://doi.org/10.4171/owr/2025/10
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.00
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article

Data Assimilation: From Mathematical and Statistical Foundations to Applications

Jana de Wiljes, Aretha L. Teckentrup, Youssef Marzouk
Oberwolfach Reports
Meteorological Phenomena and Simulations
article

Data Assimilation: From Mathematical and Statistical Foundations to Applications

Jana de Wiljes, Aretha L. Teckentrup, Youssef Marzouk
article en

Abstract

Data assimilation, where predictions from a dynamical system are updated sequentially based on new and incomplete observations, is increasingly finding applications in many areas of science and technology. This workshop brought together a collection of scientists from dynamical systems, statistics, machine learning, applied probability, uncertainty quantification, and mathematical modelling, as well as practitioners in the field.

Oberwolfach ReportsVol. 22(1)
Technische Universität Ilmenau (DE), Massachusetts Institute of Technology (US), University of Edinburgh (GB)
Openalex Percentile: Top 72%
Meteorological Phenomena and Simulations
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