Thore Kockerols

Results 31 issues of Thore Kockerols

Hi, I am looking for an arm64 container generator. Would be great to have this option as well, instead of default x86_64. Many thanks, Thore

enhancement

Hi, I tried running GenericSchur on GPU (via Google Colab) and unfortunately get stuck very early on. He is resorting to LAPACK Schur, which is not implemented for GPUs. Having...

Hi, it would be nice to have [dmperm](https://github.com/DrTimothyAldenDavis/SuiteSparse/blob/master/CXSparse/Source/cs_dmperm.c) implemented as well. I coudn't find a julia implementation and am using a python workaround for now.

The latest Krylov.jl version has a block-gmres version which I think can simplify/speed-up some parts of the code.

performance

it would be good to preserve sparsity. the culprit in the ForwardDiff extension is: ```julia y_and_dy = map(eachindex(IndexCartesian(), y)) do i Dual{T}(y[i], Partials(ntuple(k -> dy[k][i], Val(N)))) end ``` which always...

feature

in order to keep dependencies lean in downstream packages I would recommend to reexport ForwardDiffBackend() ```Julia import Reexport Reexport.@reexport import AbstractDifferentiation: ForwardDiffBackend ```

discussion

Is there any capability to solve this kind of problem: ```Julia using SymPy @syms x a b c solve(x^a * b - c, x) # 1-element Vector{Sym}: # (c/b)^(1/a) ```...

I am reexporting functions from `AxisKeys.jl` and `Aqua.jl` noticed that `Not` is exported but not defined. It would be nice to resolve this one way or another. In the meantime...

Would it be possible to change the default behavior for `@addlogprob!` and not have it included in the `PriorContext()` I understand the current solution is to do this: ```julia if...

I cannot verify your results using numderiv for non-symmetric matrices (I can for symmetric matrices). Could you implement an error that this is not implemented yet?