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### 🚀 The feature, motivation and pitch
It would be amazing if there could be support for [banded matrix](https://en.wikipedia.org/wiki/Band_matrix) operations, which are more efficiently stored by…
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In Julia 1.1.1, I have discovered a few problems with `ldiv!` and `rdiv!` when the arguments are triangular matrices. The problems are in both `triangular.jl` and `bidiag.jl`. The former source file d…
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### 🚀 The feature, motivation and pitch
Recently LDL factorization and solver were added to `torch.linalg` with https://github.com/pytorch/pytorch/pull/69828. The factorization is stored in the packe…
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```
Traceback (most recent call last):
File "/home/stratz/work/training/stratz-keras/win_rate.py", line 733, in
main()
File "/home/stratz/work/training/stratz-keras/win_rate.py", line 730…
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Issue for tracking and coordinating mlx backend work:
### `mlx.math`
- [ ] `fft`
- [ ] `fft2`
- [ ] `rfft`
- [ ] `irfft`
- [ ] `stft`
- [ ] `istft`
- [x] `logsumexp` #19578
- [ ] `qr`…
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Hi,
I would like to repeatedly solve linear systems of the form K^(-1) \* x, where x changes.
More concretely, I would like to build a theano function that just takes an x and then returns K^(-1) \* …
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```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…
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I have created a cholesky decomposition of my covariance matrix as follows: `L = T.slinalg.cholesky(self.cov)`, a 210x210 matrix. However, when I try to use `Linv_delta = T.slinalg.solve(L,T.transpose…
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```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…
-
```
Is there an easy way to implement an efficient parallel sparse triangular
matrix backsubstitution step using cusp/thrust in the library? This would
enable the utilization of more elaborate precond…