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FMI 3.0 can now be generated with tools such as Dymola. Importantly, FMI 3 introduces support for adjoint derivatives, which makes embedding FMUs in CasADi expressions potentially much more efficient.…
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The demoPDEs tests that use adjoints from Tempus started failing yesterday 11/7:
demoPDEs_Advection1D_Scalar_Param_Adjoint_Sens_Explicit
demoPDEs_Advection1D_with_Source_Dist_Param_Adjoint_Sens_…
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The adjoint operator of the wavelet transform operator is not correct in all cases. Namely, when using `pywt` wavelets, [we have redundant wavelet transforms](https://pywavelets.readthedocs.io/en/v0.4…
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The current implementation of adjoint sensitivities is functional, but very poorly optimized. Currently it just evaluates the full derivative function for the domain and then extracts the one derivati…
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For most of our operators an adjoint/derivative method will be defined. pytorch.autograd should use that. If the method is not defined it should default to standard pytorch.autgrad. More details can b…
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Luckily, adjoint methods for (most) eigenvalue problems tend to be rather trivial _if you are optimizing the eigenvalue directly_. So, for example, if you want to match the effective index of two mode…
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**Describe the bug 🐞**
The `sensealg` in solve is ignored, currently it only follows the sensealg defined in the problem
Looks like, the sensealg is not in the prob.kwargs, and is ignored in the…
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The gradient here should be one, not `nothing`:
```julia
julia> using Zygote
julia> Zygote.gradient(x -> (x:3)[1], 1.2)
(nothing,)
julia> 1.2:3
1.2:1.0:2.2
```
It looks like the adjoint fo…
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Hello,
I tried running the nufft on GPU in "DFT" mode with options "-g -s". This leads to an error "Command exited with error code -11". If I run the adjoint DFT with options "-g -s -a", the code …