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Journal Article

Low-Rank Eigenvector Compression of Posterior Covariance Matrices for Linear Gaussian Inverse Problems

MPS-Authors
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Benner,  Peter
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Qiu,  Yue
Computational Methods in Systems and Control Theory, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Stoll,  Martin
Numerical Linear Algebra for Dynamical Systems, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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benner_2474802.pdf
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Citation

Benner, P., Qiu, Y., & Stoll, M. (2018). Low-Rank Eigenvector Compression of Posterior Covariance Matrices for Linear Gaussian Inverse Problems. SIAM/ASA Journal on Uncertainty Quantification, 6(2), 965-989. doi:10.1137/17M1121342.


Cite as: http://hdl.handle.net/21.11116/0000-0000-2E2A-F
Abstract
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