-
Hello
I am currently using autodiff for a planning problem where gradient calculation is very time critical and it appears that my application spends most of the time during the gradient calculatio…
-
Dear devs,
recently I have been trying to differentiate complicated expressions that eventually result in nested calls to `pow`. I find that the forward mode derivative for these cases is not taken…
-
In the definition of type `Real`:
~~~c++
template
class Real
{
...
};
~~~
Ensure `T` is a numeric type (not necessarily standard number types such as float, double, but also permit other c…
-
I'm running into some trouble applying `optimistix.least_squares(fn, LevenbergMarquardt(...), x0)` to certain problems. From the error message below, my understanding of the root cause is that forward…
-
I'm a newbie using the autodiff library and more general using automatic differentiation in general. I was trying to implement gradient computation for a simple Gauss-Seidel type solver. It runs fine …
-
Is it possible to use std::complex as a custom scalar type in reserve mode? Can you add an example?
-
Hello! I've been lurking around this package for a while, thinking of maybe using it instead of `SaticArrays.jl`, or maybe what I want is a little different and I should try to do something similar b…
-
## Description
@WardBrian brought up the idea of adding an ARCHITECTURE.md file to each of the Stan repos and I really like the idea. A long blog about these files can be found [here](https://matkl…
-
# Summary
At present, any given mathematical expression in `aegir` is formed as a (potentially very large) tree vis-a-vis symbolic differentiation. This leads to many challenges, but doesn't have t…
-
Is it not sufficient to directly take gradients of U0 w.r.t x?
I think i am missing something here..
much obliged if someone could clear it.
Thanks