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Hello,
I tried using the adjoint-family integrators to obtain sensitivities of an arbitrary cost functional
![](https://latex.codecogs.com/gif.latex?%5Cbegin%7Balign*%7D%20%5CPsi%28%5Cvec%7Bp%7D%29%…
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**Describe the bug 🐞**
I'm trying to implement a discrete callback which changes the value of a parameter. I'm using ComponentArrays for the parameters as my application is for large systems with c…
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I wanted to try something simple with [SciMLSensitivity.jl](https://github.com/SciML/SciMLSensitivity.jl) to find the sensitivities of the solution to a `LinearProblem` with respect to parameters. How…
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```
The following list of SfePy Terms still need examples:
d_acoustic_alpha
d_acoustic_surface
d_of_ns_min_grad1
d_of_ns_min_grad2
d_of_ns_surf_min_d_press
d_sa_acoustic_alpha
d_sa_acoustic_alpha2
d_…
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```
The following list of SfePy Terms still need examples:
d_acoustic_alpha
d_acoustic_surface
d_of_ns_min_grad1
d_of_ns_min_grad2
d_of_ns_surf_min_d_press
d_sa_acoustic_alpha
d_sa_acoustic_alpha2
d_…
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Currently, Meep gradients may only be computed within a `DesignRegion`, where the material distribution is defined by a bilinear interpolation of a density from a numpy array.
However, it would be …
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When computing the Jacobian of `MX x = vertcat(...)` using reverse mode AD or forward mode AD, different C code is generated. Both implementations can introduce for loops in the code even if the origi…
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Consider a case where we have a function `f: ℝᵐ → ℂʳ → ℂˢ → ℝⁿ = ℝᵐ → ℝⁿ`, which we can write as `f = f₃ ∘ f₂ ∘ f₁`.
Typically `f₁` will produce a complex output by adding, subtracting, multiplying o…
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Hi,
I’m using this amazing package to get the sensitivities of a SDE problem. Unfortunately, the results I obtain are not correct. I know that are not correct because I can compare them with analy…
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Backproping through `getindex` is pretty slow at the minute, due to the need to make copies of the entire array on the reverse-pass, and to fill it with zeros. The current implementation basically has…