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While desperately searching the web for good explanations on adjoints I found this gem on the internet:
```
Mantzaflaris, A., Jüttler, B., Khoromskij, B. N., & Langer, U. (2017). Low rank tensor met…
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For each adjoint method, it would be convenient to include a table specifying which are compatible with each kind of autodifferentiation.
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**Add testing metrics to be used for testing package functions**
Difficulty:
- Medium
Metric list:
- Mean squared error, this can be used to evaluate round-trip error e.g. `x -> x' = inverse( forw…
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First off, thank you for this excellent library! It has been invaluable in my work on radio astronomy imaging.
I am working on some imaging methods that are iterative, and I would like to use the r…
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**Describe the bug**
I experimented an increased memory usage any time firedrake.adjoint or firedrake_adjoint (deprecated) is imported.
Here below a minimal working example showing the issue. Simila…
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```Futhark
def dficfj_test_ad (x : [8]f64) =
#[unsafe] -- For simplicity of generated code.
let col_w_pre_red =
tabulate_3d 4 2 4 (\ k i j -> x[k+j]*x[i+j])
let col_w_red =
map (ma…
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Hi! I found that when I don't jit the solver and use `solver.solve` instead of `jit_solver.solve`, the code raises the following error.
```
Traceback (most recent call last):
File "/apdcephfs/sha…
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@donskerclass Should we do this with student-t shocks or gaussian? Guassian might be a little easier for simulation/etc. so my preference is for that (unless gaussian changes whether this is a usef…
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Using `__solve` as mentioned in https://docs.sciml.ai/DiffEqDevDocs/stable/contributing/adding_packages/ allows the package to use the DiffEqBase.jl high level solve handling:
https://github.com/Sc…
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Hi @willtebbutt,
From the ToDo list #59 I have tried to go ahead with the periodic kernel as proposed by [Solin & Särkkä (2014)](http://proceedings.mlr.press/v33/solin14.pdf). The periodic kernel i…