SFB 1294
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    • Research Area A Theory and Algorithms
      • A01 Statistics for stochastic partial differential equations
      • A02 Long-time stability and accuracy of ensemble transform filter algorithms
      • A03 Sequential and adaptive learning under dependence and non-standard objective functions
      • A04 Nonlinear statistical inverse problems with random observations
      • A05 Combining non parametric statistical and probabilistic approaches for inference on cloud-of-points data
      • A06 Approximative Bayesian inference and model selection for stochastic differential equations (SDEs)
      • A07 Model order reduction for Bayesian inference
    • Research Area B Algorithms and Applications
      • B02 Inferring the dynamics underlying protrusion-driven cell motility
      • B03 Parameter inference and model comparison in dynamical cognitive models
      • B04 Parametric and nonparametric modeling of spatiotemporal change patterns in seismicity using Hawkes processes
      • B05 Attention selection and recognition in scene-viewing
      • B06 Novel methods for the 3D reconstruction of the dynamic evolution of the Van Allen belts using multiple satellite measurements
      • B07 Inferring active particle dynamics by data assimilation
      • B08 Continuous learning by integrating reinforcement learning and data assimilation to individualise drug treatments
      • B09 Neural network modelling of brain responses during language comprehension
    • Research Area Z Common Activities
      • Z03 Information Infrastructure for data assimilation
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  1. Data assimilation - the collaborative research centre SFB1294
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Colloquia in 2025

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17Jan2025

Model Reduction in Pharmacology: Bridging Biological Understanding and Statistical Analysis

Jane Knöchel, InSilicoTrials, Sweden 2.28.0.10810:15 - 11:45

Quantitative system pharmacology models (QSP) are a subset of mathematical models focused on drug pharmacology. They integrate datasets from diverse…

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02Apr2025

'Sparsity: The key to tackling large-scale least squares problems’ and 'Numerical linear algebra for data assimilation'

Jennifer Scott & Jemima Tabeart 2.27.1.0114:00-15:30

An additional colloquium with Jennifer Scott (STFC Rutherford Appleton Laboratory and The University of Reading, UK) and Jemima Tabeart (TU Eindhoven)…

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06Jun2025

The Fundamental Subspaces of Ensemble Kalman Inversion

Elizabeth Qian, Georgia Tech 2.28.0.10810:15 - 11:45

The Ensemble Kalman Inversion (EKI) method re-interprets the ensemble Kalman filter as an adjoint/derivative-free iterative method for solving least…

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27Jun2025

Causal inference: A very short intro

Jakob Runge, University of Potsdam 2.28.0.10810:15 - 11:45

Machine learning excels in learning associations and patterns from data and is increasingly adopted in natural-, life- and social sciences, as well as…

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18Jul2025

Comparing Neural Representations

Heiko Schütt, University of Luxembourg 2.28.0.10810:15 - 11:45

In computational neuroscience and machine learning, we develop more and more complex deep neural network models to mimic the human brain and to solve…

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23Sep2025

7th Kálmán Lecture

Daniela Calvetti, Case Western Reserve University, USA tjatba

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Current Colloquia
  • Overview Colloquia Summer Term 2025

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Institute of Mathematics

SFB 1294 – Data Assimilation
Institute of Mathematics
Karl-Liebknecht-Str. 24-25
14476 Potsdam - OT Golm

SFB1294[at]uni-potsdam.de
+49 331 977 203137

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