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It should be possible to `deriv()` a `Polynomial` to get its derivative.
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Simple example that should have been possible:
X ~ Uniform(a,b)
Y ~ Uniform(c,d)
X,Y are independent. Then:
Z = X + Y
has some trapezoidoid (🙃) distribution over (a+c,b+d).
I would like to be …
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## 🚀 Feature
From what I've seen (please correct me if I'm wrong), pytorch_geometric assumes that the output of a neural network is a number rather than a graph. What if the output is another graph…
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# Context
Documenting field-level explicit likelihood inference from a differentiable cosmological model.
In [code](https://github.com/hsimonfroy/montecosmo/blob/a7346788b5555b2f6b14bff3e9dc2f4c9…
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I am implementing my own `ZerothOrderOptimizer` and have the suspicion that
https://github.com/JuliaNLSolvers/Optim.jl/blob/38cfbe895dc8126ae029c5d3165d92b6232f3bd4/src/api.jl#L87
should be
`…
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### Improving the quality of the plots
It would be great if we could see a few special points like (discontinuous, non-differentiable, maximum and minimum) points being pinned in the plots.
Somet…
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[Deep Adaptive LiDAR: End-to-end Optimization of Sampling and Depth Completion at Low Sampling Rates](https://ieeexplore.ieee.org/abstract/document/9105252)
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It seems that the generic_potential.py module does not include the daisy improved corrections. Are there any way to improve this? Or this package actually have this?
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I have checked the documentation and I realized that many surrogate functions exist. My question is, is there anyway to have the one used by SLAYER https://arxiv.org/pdf/1810.08646.pdf ?
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```julia
struct MyStruct
a
end
(m::MyStruct)(t) = m.a
@scalar_rule (m::Struct)(t) one(m.a)
```
Results in `UndefVarError: m not defined`.
As per the docs, this should not work. @ox…