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Bayesian bilevel operator learning with low-rank adaptation for efficient uncertainty quantification of PDE inverse problems. [PDF]
Nat CommunZhang RZ, Miles CE, Xie X, Lowengrub JS.
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SIAM Journal on Numerical Analysis, 1993
The inverse interval matrix is defined as the narrowest interval matrix containing the inverses of all the matrices from a given interval matrix. Both theoretical and practical results concerning computation of the inverse interval matrix are presented. In particular, explicit formulas are given for the inverse of an interval matrix with radius of rank
J Rohn
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The inverse interval matrix is defined as the narrowest interval matrix containing the inverses of all the matrices from a given interval matrix. Both theoretical and practical results concerning computation of the inverse interval matrix are presented. In particular, explicit formulas are given for the inverse of an interval matrix with radius of rank
J Rohn
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The Inverse of Circulant Matrix
Applied Mathematics and Computation, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fuyong Lin
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Communications in Statistics, 1973
Elements of the information matrix for the variance components of a linear model involve, under normality, the inverse of the variance-covariance matrix of the vector of observations. Attempts at finding this inverse for the 2-way crossed classification random model, unbalanced data, are described.
Searle, S. R., Rudan, J. W.
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Elements of the information matrix for the variance components of a linear model involve, under normality, the inverse of the variance-covariance matrix of the vector of observations. Attempts at finding this inverse for the 2-way crossed classification random model, unbalanced data, are described.
Searle, S. R., Rudan, J. W.
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Matrix inversion by partitioning
Proceedings of the 1952 ACM national meeting (Toronto) on - ACM '52, 1952There is presently available a large number of techniques purporting to accomplish the inversion of matrices. While the purely mathematical aspects of this problem, on one hand, are thus well recognized, the computational ones, on the other hand, are not.
Mark Lotkin, R. Remage
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