This image shows Michael Sinsbeck

Michael Sinsbeck

Dr.-Ing.

Postdoc
Institute for Modelling Hydraulic and Environmental Systems (LS3/SimTech)

Contact

+49 711 685 60119

Business card (VCF)

Pfaffenwaldring 5a
D-70569 Stuttgart
Room: 2.01

  1. 2021

    1. Sinsbeck M, Cook E, Nowak W. Sequential Design of Computer Experiments for the Computation of Bayesian Model Evidence. SIAM/ASA Journal on Uncertainty Quantification. 2021 Feb;9(1):260--279.
    2. González-Nicolás A, Schwientek M, Sinsbeck M, Nowak W. Characterization of export regime in discharge-concentration plots via an advanced time-series model and event-based sampling. Water. 2021;13:1723.
  2. 2020

    1. Sinsbeck M, Höge M, Nowak W. Exploratory-phase-free estimation of GP hyperparameters in sequential design methods - at the example of Bayesian inverse problems. Frontiers in Artificial Intelligence, section AI in Food, Agriculture and Water. 2020;3(52):1–16.
    2. Gonzalez-Nicolas Alvarez A, Nowak W, Sinsbeck M, Schwientek M. Characterize the catchment regime by applying optimal monitoring strategies. In: EGU General Assembly Conference Abstracts. 2020. p. 4843. (EGU General Assembly Conference Abstracts).
  3. 2019

    1. González-Nicolás A, Nowak W, Sinsbeck M, Schwientek M. Optimal scheduling and event-based sampling: development and demonstration for investigating the nitrate characteristics of a headwater catchment. In: General Assembly 2019, Geophysical Research Abstracts: EGU2019-964, 2019. Vienna, Austria: European Geosciences Union (EGU); 2019. (General Assembly 2019, Geophysical Research Abstracts: EGU2019-964, 2019).
  4. 2017

    1. Sinsbeck M, Nowak W. Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems. In Weimar, Germany: 88th GAMM Annual Meeting; 2017.
  5. 2016

    1. Sinsbeck M, Nowak W. Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems. In Lausanne, Switzerland: SIAM Conference on Uncertainty Quantification; 2016.
  6. 2015

    1. Sinsbeck M, Nowak W. An optimal sampling rule for nonintrusive polynomial chaos expansions of expensive models. International Journal for Uncertainty Quantification. 2015;5(3):275–95.
    2. Sinsbeck M, Tartakovsky D. Impact of Data Assimilation on Cost-Accuracy Tradeoff in Multi-Fidelity Models at the Example of an Infiltration Problem. In: General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-11902, 2015. Vienna, Austria: European Geosciences Union (EGU); 2015. (General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-11902, 2015).
    3. Sinsbeck M, Tartakovsky D. Impact of data assimilation on cost-accuracy tradeoff in multifidelity models. SIAM/ASA Journal of Uncertainty Quantification. 2015;3(1):954–68.
  7. 2014

    1. Sinsbeck M, Nowak W. Adaptive Sampling for Bayesian Updating with Non-Intrusive Polynomial Chaos Expansions. In Savannah, Georgia, USA: SIAM Conference on Uncertainty Quantification; 2014.
  8. 2012

    1. Sinsbeck M. Adaptive grid refinement for two phase flow in porous media. Institute for Modelling Hydraulic and Environmental Systems, Universität Stuttgart. Diploma Thesis. 2012.

03/2012 - 09/2016 Phd Student, Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart
Since 01/2017 Postdoc, Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart

Uncertainty quantification and Bayesian Inverse Problems for computationally expensive simulations

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