Data Assimilation: From Mathematical and Statistical Foundations to Applications

  • Jana de Wiljes

    Technische Universität Ilmenau, Germany
  • Youssef Marzouk

    Massachusetts Institute of Technology, Cambridge, USA
  • Aretha Teckentrup

    University of Edinburgh, UK
Data Assimilation: From Mathematical and Statistical Foundations to Applications cover
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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.

Cite this article

Jana de Wiljes, Youssef Marzouk, Aretha Teckentrup, Data Assimilation: From Mathematical and Statistical Foundations to Applications. Oberwolfach Rep. 22 (2025), no. 1, pp. 451–484

DOI 10.4171/OWR/2025/10