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In `Zygote.jl`, we can take the gradient with respect to all fields of a struct `foo` passed through a function `bar` via
```julia
g = Zygote.gradient(f -> bar(f), foo)
```
Can this be done in…
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I think it would be great to add [dual number](https://en.wikipedia.org/wiki/Dual_number) support to numpy. Dual numbers are numbers a + b ε where ε^2 = 0. These numbers have great utility in auto…
tBuLi updated
4 years ago
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See my [gist](https://gist.github.com/jwscook/a8be5c11440981d6de2270a7bf633551) for what I'm trying to achieve.
I'm using NLsolve to find the cartesian coordinates given curvilinear coordinates and…
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As it stands the following overloads seem to be problematic, and restrict the type to work only for real types:
```C++
template constexpr auto abs2(R&& r) { return std::forward(r) * std::forward(r);…
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**Is your feature request related to a problem? Please describe.**
The problem is described here: https://discourse.julialang.org/t/how-to-use-scimloperators-jl-with-autograd-in-differentialequatio…
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- we currently use [ForwardDiff](https://github.com/JuliaDiff/ForwardDiff.jl) but should be able to move transparently (= without any user code change) to another backend
- [x] use the backend choice…
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Is it on purpose that values of complex or dual types are not shown? (But arrays of those element types are shown?)
MWE (v0.7):
```julia
using Parameters, DualNumbers
@with_kw struct Para
a =…
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Please consider looking into adding platform support for the new RP2350 MCU and the Raspberry Pi Pico 2 development board.
RP2350 is the successor and next-generation of RPi RP2040 so guess would n…
Hedda updated
2 weeks ago
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```julia
julia> using ForwardDiff, LabelledArrays
julia> SLVector(a=2.0,b=ForwardDiff.Dual(1,2))
2-element SLArray{Tuple{2},Real,1,2,(:a, :b)}:
2.0
Dual{Nothing}(1,2)
```
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I ran into the following problem today:
```julia
function tensor_exp(A::SymmetricTensor{2})
E = eigen(A)
A_exp = zero(A)
for (i, λ) in enumerate(E.values)
N = E.vectors[:,i]
…