-
Schur decomposition is implemented efficiently on GPU in PyTorch, Jax, and MatLab. It is an essential ingredient for the efficient computation of matrix square root (sqrtm).
It would be ideal to ha…
-
I am aware of PR #904 that will add generic eigenvalue solving to all backends - awesome! Can't wait!
In the meantime, a smaller subset of eigenvalue problems are those where the matrix is upper H…
ibell updated
7 years ago
-
Thanks for maintaining the package. It is very useful, yet missing a crucial part for my applications: Schur(qz) decomposition - e.g.
`QZ::qz(QZ::exAB2$A, QZ::exAB2$B)`
I did not find any implemen…
-
For non symmetric systems, a Schur decomposition instead of an eigenvalue decomposition is used internally. This is a preparation for the non-symmetric case.
-
There are a handful of eigenproblem decompositions that I would like to use but are not provided by PyTorch (e.g. Hessenberg and Schur). This is one area where PyTorch noticeably lags behind other app…
-
First of all, thanks for this package. I made some slight modifications to account for the recent changes of Julia (see my forked [repo](https://github.com/FuZhiyu/Gensys.jl)). It significantly saved …
-
### Problem Description
Currently, the diagonalization of the propagator matrix in order to get floquet eigenstates is not accurate, since the eig function from scipy provides the right eigenvectors …
-
`VARMAX` errors out with a Schur decomposition error in one of the tests, see here:
https://github.com/alan-turing-institute/sktime/runs/7673800745?check_suite_focus=true
only on windows
In that …
-
The transformation matrices from the MB03WD periodic Schur decomposition are not computed correctly when the period P increases. The slicot example TMB03WD can be used to reproduce the problem, see at…
-
Some applications require an arbitrary sorting of eigenvalues in a Schur decomposition. Currently, `ordschur` supports re-ordering with a logical `select` vector that effectively groups the eigenvalu…