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2A unified framework for quantitative interdisciplinary flood risk assessment
A. Guthke, A. Bakhshipour, F. de Barros, H. Class, J. Daniell, U. Dittmer, J. Haas, M. Friedrich, C. Kropp, B. Merz and 7 other author(s). (December 2020)
4 years ago by @ls3
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1Diagnosing Model-structural Errors with a Sliding Time-window Bayesian Analysis
H. Hsueh, A. Guthke, T. Wöhling, and W. Nowak. (December 2020)
4 years ago by @ls3
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IWSMONTH:12IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSYEAR:2020IWSTYPENR:3from:timothypraditia2IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSAUTHOR:HsuehHan-FangIWSABT:ls3IWSAUTHOR:GuthkeAnneli
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1Providing relevant uncertainty information to decision makers: Subjective post-processing of rigorous Bayesian uncertainty assessment of model projections
C. Jackisch, A. Schibalski, B. Schröder, W. Nowak, and A. Guthke. (December 2020)
4 years ago by @ls3
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2Overcoming the Model-to-Experimental Data Fit Problem in Porous Media: a New Quantitative Method to Evaluate and Compare Models
I. Banerjee, A. Guthke, C. Ven, K. Mumford, and W. Nowak. (December 2020)
4 years ago by @ls3
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IWSAUTHOR:BanerjeeIshaniIWSMONTH:12IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSYEAR:2020IWSTYPENR:3from:timothypraditia2IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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3Working with multi-model ensembles - what makes models differ and how can we visualize ensembles?
A. Schäfer-Rodrigues-Silva, T. Seitz, A. Guthke, and W. Nowak. Tübingen, Germany, Seminar of the Research Training Group "Integrated Hydrosystem Modelling", (June 2018)
5 years ago by @ls3
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3How reliable is Bayesian model averaging under noisy data? Statistical assessment and implications for robust model selection
A. Schöniger, T. Wöhling, and W. Nowak. General Assembly 2014, Geophysical Research Abstracts 16: EGU2014-2211, 2014, Vienna, Austria, European Geosciences Union (EGU), (27 April - 02 May 2014)
5 years ago by @ls3
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3How model selection and averaging strategies help us improve hydrological models
A. Guthke, M. Höge, and W. Nowak. General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-12797, 2018, Vienna, Austria, European Geosciences Union (EGU), (April 2018)
5 years ago by @ls3
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IWSAUTHOR:GuthkeAnneli
IWSMONTH:4IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSTYPENR:3from:timothypraditiaIWSAUTHOR:HögeMarvinfrom:jannikhaasIWSYEAR:20182IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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4Bayesian model selection under computational time constraints: application to river modeling
A. Guthke, S. Oladyshkin, F. Mohammadi, R. Kopmann, and W. Nowak. Fall Meeting 2018, Washington, D.C., USA, American Geophysical Union (AGU), (December 2018)
5 years ago by @ls3
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IWSYEAR:2018
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IWSAUTHOR:NowakWolfgang
IWSSUBTYPE:inproceedings
3
IWSABT:ls3
IWSAUTHOR:GuthkeAnneli
IWSMONTH:12IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSAUTHOR:OladyshkinSergeyIWSTYPENR:3from:timothypraditiafrom:jannikhaasIWSYEAR:20182IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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3Which level of model complexity is justified by your data? A Bayesian answer
A. Schöniger, W. Illman, T. Wöhling, and W. Nowak. General Assembly 2016, Geophysical Research Abstracts 20: EGU2016-12413, 2016, Vienna, Austria, European Geosciences Union (EGU), (April 2016)
5 years ago by @ls3
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IWSABT:ls3
IWSAUTHOR:GuthkeAnneli
IWSMONTH:4IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSTYPENR:3from:timothypraditiafrom:jannikhaasIWSYEAR:20162IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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3Model selection under computational time constraints: application to river engineering
S. Oladyshkin, A. Guthke, F. Mohamadi, R. Kopmann, and W. Nowak. Saint-Malo, France, XXII. International Conference on Computational Methods in Water Resources (CMWR), (June 2018)
5 years ago by @ls3
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IWSAUTHOR:GuthkeAnneli
IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSMONTH:6IWSAUTHOR:OladyshkinSergeyIWSTYPENR:3from:timothypraditiafrom:jannikhaasIWSYEAR:20182IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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3The importance of model similarity in multi-model problems
A. Schäfer-Rodrigues-Silva, A. Guthke, and W. Nowak. Stuttgart, Germany, Meeting of the international doctoral program "Environment Water", (February 2018)
5 years ago by @ls3
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IWSABT:ls3
IWSAUTHOR:GuthkeAnneli
IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSTYPENR:3IWSMONTH:2from:timothypraditiafrom:jannikhaasIWSYEAR:20182IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedingsIWSAUTHOR:Schäfer-Rodrigues-SilvaAlineIWSABT:ls3IWSAUTHOR:GuthkeAnneli
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3How to address measurement noise in Bayesian model averaging
A. Schöniger, T. Wöhling, and W. Nowak. Fall Meeting 2014, Abstract: H23K-1017, San Francisco, CA, USA, American Geophysical Union (AGU), (December 2014)
5 years ago by @ls3
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IWSMONTH:12IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSTYPENR:3from:timothypraditiafrom:jannikhaasIWSYEAR:20142IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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2Prediction of pure component and mixture viscosities using PCP-SAFT and entropy scaling
O. Lötgering-Lin, M. Hopp, J. Gross, A. Schöniger, and W. Nowak. Houston, TX, USA, SAFT 2015, (May 2015)
5 years ago by @ls3
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3Do Bayesian model weights tell the whole story? New analysis and optimal design tools for maximum-confidence model selection
A. Schöniger, and W. Wöhling. Fall Meeting 2013, Abstract: H33J-02, San Francisco, CA, USA, American Geophysical Union (AGU), (December 2013)
5 years ago by @ls3
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IWSYEAR:2013IWSMONTH:12IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSTYPENR:3from:timothypraditiafrom:jannikhaas2IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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2Quantifying and visualizing similarity in multi-model ensembles
A. Schäfer-Rodrigues-Silva, T. Seitz, A. Guthke, and W. Nowak. Cargese, France, Summer school on "Flow and Transport in Porous and Fractured media", (June 2018)
5 years ago by @ls3
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3On the various (good and bad) ways to evaluate Bayesian model weights
A. Schöniger, T. Wöhling, L. Samaniego, and W. Nowak. General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-2084-2, 2015, Vienna, Austria, European Geosciences Union (EGU), (April 2015)
5 years ago by @ls3
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IWSMONTH:4IWSTYPEEN:contribution_to_edited_volumesIWSTYPEDE:KonferenzbeiträgeIWSTYPENR:3from:timothypraditiafrom:jannikhaasIWSYEAR:20152IWSAUTHOR:NowakWolfgangIWSSUBTYPE:inproceedings3IWSABT:ls3IWSAUTHOR:GuthkeAnneli
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3Lessons learned from a past series of Bayesian model averaging studies for soil/plant models
W. Nowak, T. Wöhling, and A. Schöniger. General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-10293-1, 2015, Vienna, Austria, European Geosciences Union (EGU), (April 2015)
5 years ago by @ls3
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3Quantifying similarity in multi-model ensembles
A. Schäfer-Rodrigues-Silva, A. Guthke, and W. Nowak. Tübingen, Germany, International Conference on Integrated Hydrosystem Modelling, (April 2018)
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2A unified framework for quantitative interdisciplinary flood risk assessment

1Diagnosing Model-structural Errors with a Sliding Time-window Bayesian Analysis

1Providing relevant uncertainty information to decision makers: Subjective post-processing of rigorous Bayesian uncertainty assessment of model projections

2Overcoming the Model-to-Experimental Data Fit Problem in Porous Media: a New Quantitative Method to Evaluate and Compare Models

3Working with multi-model ensembles - what makes models differ and how can we visualize ensembles?

3How reliable is Bayesian model averaging under noisy data? Statistical assessment and implications for robust model selection

3How model selection and averaging strategies help us improve hydrological models

4Bayesian model selection under computational time constraints: application to river modeling

3Which level of model complexity is justified by your data? A Bayesian answer

3Model selection under computational time constraints: application to river engineering

3The importance of model similarity in multi-model problems

3How to address measurement noise in Bayesian model averaging

2Prediction of pure component and mixture viscosities using PCP-SAFT and entropy scaling

3Do Bayesian model weights tell the whole story? New analysis and optimal design tools for maximum-confidence model selection

2Quantifying and visualizing similarity in multi-model ensembles

3On the various (good and bad) ways to evaluate Bayesian model weights

3Lessons learned from a past series of Bayesian model averaging studies for soil/plant models

3Quantifying similarity in multi-model ensembles

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