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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Seminars in 2017

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14Jul2017

Adaptive convergence results for numerical efficient Bayesian methods

Jan van Waaj, University of Amsterdam, Netherlands 2.28.0.108

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21Aug2017

Minimization-based sampling from the posterior distribution for inverse problems with Gaussian prior distributions

Dean S. Oliver, Uni Centre for Integrated Petroleum Research, Bergen, Norway 2.09.0.1410:15-11:45

Inverse problems for subsurface ow are typically characterized by large numbers of para- meters (e.g. coef cients of PDEs describing ow and transport)…

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28Aug2017

Phase transition in mean-field games: An application to synchronization of coupled oscillators

Prashant Mehta, University of Illinois at Urbana-Champaign, USA 2.09.014Begin: 14:00

This talk is concerned with phase transition and self-organization in mean-field games.

The motivation comes from the following sequence of events…

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15Sep2017

Improving Data Assimilation by Surfing the Waves

Juan Restrepo, Oregon State University, USA 2.28.2.12310:15-11:45

The use of models and data, via data assimilation, is one ofthe strategies pursued to improve climate and weather predictions and retrodictions. In…

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24Nov2017

On the use of the particle filter for geomechanical parameter estimation when monitoring subsidence due to hydrocarbon extraction

Femke Vossepoel, Delft University of Technology, Netherlands 2.28.0.10410:15-11:15

Fluid extraction from a subsurface hydrocarbon reservoir results in compaction of the reservoir, in particular cases leading to subsidence and induced…

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01Dec2017

A class of nonlinear filters induced by local couplings

Alessio Spantini, Massachusetts Institute of Technology (MIT), USA 2.28.0.10410:15-11:15

We introduce a class of structure-exploiting nonlinear filters for high-dimensional state-space models with intractable transition kernels. The idea…

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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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