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A Bayesian approach for continuous improvement of kinetic parameter estimates

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Rätze,  Karsten
International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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McBride,  Kevin
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Sundmacher,  Kai
Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
Otto-von-Guericke-Universität Magdeburg, External Organizations;

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Rätze, K., McBride, K., & Sundmacher, K. (2019). A Bayesian approach for continuous improvement of kinetic parameter estimates. Talk presented at 12th European Congress of Chemical Engineering – ECCE 12. Florence, Italy. 2019-09-15 - 2019-09-19.


Cite as: https://hdl.handle.net/21.11116/0000-0005-6596-0
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