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This repository has been archived by the owner on Apr 18, 2023. It is now read-only.
The sensitivities for / and \ seem to match the definitions for matrix inverse products in the Giles paper, and they work as tested on square matrices. However, the formulas in the paper assume that the matrix is invertible, which also implies that it's square. Julia itself does not impose such a restriction; / and \ are defined for rectangular matrices. The sensitivities for the matrix inverse product no longer apply in that case though:
julia> n, m = 3, 4;
julia> A = randn(m, n); B = randn(m, n); Ȳ = randn(size(A / B));
julia> check_errs(/, Ȳ, (A, B), (randn(size(A)), randn(size(B))))
ERROR: "</> allocated": large deviation from reference:
relative error: 8.757e-01
tolerance: 1.000e-07
absolute error: 1.153e+02
tolerance: 1.000e-10
which means we'll need to reformulate our sensitivities for / and \.
The text was updated successfully, but these errors were encountered:
The sensitivities for
/
and\
seem to match the definitions for matrix inverse products in the Giles paper, and they work as tested on square matrices. However, the formulas in the paper assume that the matrix is invertible, which also implies that it's square. Julia itself does not impose such a restriction;/
and\
are defined for rectangular matrices. The sensitivities for the matrix inverse product no longer apply in that case though:which means we'll need to reformulate our sensitivities for
/
and\
.The text was updated successfully, but these errors were encountered: