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    Tensor completion for PDEs with uncertain coefficients and Bayesian Update

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    Litvinenko_SIAMCSE.pdf
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    1.322Mb
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    PDF
    Description:
    tensor completion for PDEs with uncertain coefficients and Bayesian update
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    Type
    Presentation
    Authors
    Litvinenko, Alexander cc
    KAUST Department
    Extreme Computing Research Center
    Center for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ)
    Date
    2017-03-05
    Permanent link to this record
    http://hdl.handle.net/10754/623695
    
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    Abstract
    In this work, we tried to show connections between Bayesian update and tensor completion techniques. Usually, only a small/sparse vector/tensor of measurements is available. The typical measurement is a function of the solution. The solution of a stochastic PDE is a tensor, the measurement as well. The idea is to use completion techniques to compute all "missing" values of the measurement tensor and only then apply the Bayesian technique.
    Sponsors
    ECRC KAUST, SRI UQ KAUST
    Conference/Event name
    SIAM CSE Conference
    Additional Links
    http://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=61237
    Collections
    Extreme Computing Research Center; Presentations

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