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

We consider the problem of efficient computations of the covariance matrix of the posterior probability density for linear Gaussian Bayesian inverse problems. When the probability density of the no...

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