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Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations - MaRDI portal

Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations (Q3095066)

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Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations
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    Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations (English)
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    28 October 2011
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    large-scale statistical inverse problem
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    Bayesian inference
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    uncertainty quantification
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    fast algorithms
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    low-rank approximation
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    Lanczos
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    Hessian
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    convection-diffusion
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    contaminant transport
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