Monday, July 4
Alexandre JANON, Université Paris-Sud

Sensitivity analysis and dimension reduction Mathematical models seldom represent perfectly the reality of studied systems, due to, for instance, uncertainties on the parameters that define the system. For instance, in geophysical fluids modelling, these parameters can be, e.g., the domain geometry, the initial state, the wind stress, the friction or…

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Monday, April 18
Zdenek STRAKOS, Charles University in Prague

Krylov subspace methods from the analytic, application, and computational perspective Krylov subspace methods are fascinating mathematical objects that integrate many lines of thought and are linked with hard theoretical challenges. Krylov subspace methods can be seen as highly nonlinear model reduction that can be very efficient in some cases and…

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Monday, April 4
Philippe MOIREAU (M3DISIM), Inria Saclay Ile de France

Observer strategies for inverse problems, applications to cardiology We present an original class of strategy to perform estimation for evolution equations with uncertain initial conditions and parameters. We adopt a filtering approach on the dynamical system formulation to construct a joint state-parameter estimator that uses some measurements available in standard…

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