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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Section: Application Domains

Algorithmic Differentiation

Algorithmic Differentiation of programs gives sensitivities or gradients, useful for instance for :

  • optimum shape design under constraints, multidisciplinary optimization, and more generally any algorithm based on local linearization,

  • inverse problems, such as parameter estimation and in particular 4Dvar data assimilation in climate sciences (meteorology, oceanography),

  • first-order linearization of complex systems, or higher-order simulations, yielding reduced models for simulation of complex systems around a given state,

  • adaption of parameters for classification tools such as Machine Learning systems, in which Adjoint Differentiation is also known as backpropagation.

  • mesh adaptation and mesh optimization with gradients or adjoints,

  • equation solving with the Newton method,

  • sensitivity analysis, propagation of truncation errors.