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.
Authors
- Jana de Wiljes (ORCID: https://orcid.org/0000-0002-9636-1147)
- Aretha L. Teckentrup (ORCID: https://orcid.org/0000-0001-5089-0476)
- Youssef Marzouk (ORCID: https://orcid.org/0000-0001-8242-3290)
Institutions
- Technische Universität Ilmenau (DE)
- Massachusetts Institute of Technology (US)
- University of Edinburgh (GB)
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