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Hi!
This is a follow-up on #181. The use case is to evaluate the derivatives (e.g. gradient, hessian) of some loss function $\mathcal{L}$ with respect to some variable $\theta$ at the gradient equi…
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An effort to create a very simple Decapode, to help simplify diagnosing autodiff through decapode issues.
This is a 1-D harmonic oscillator Decapode:
```
using Catlab
using Catlab.Graphics
using…
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This one puzzles me, and I suspect it's a bug. If I expand the calls to pow2(x), the code compiles and works, but if I don't, I get the error below:
``` C++
// C++ includes
#include
// autod…
ibell updated
4 years ago
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**Describe the bug**
A clear and concise description of what the bug is, ideally within 20 words.
The same algorithm of different forms produces different gradients.
**To Reproduce**
Pleas…
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A few comments for consideration in the matrix autodiff design document.
1. As much as the matrix of vars enables better performance it also greatly facilities the implementation matrix-valued reve…
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Turns out there is a (sort of) library "autodiff" inside Eigen 3.4.0.
I added Eigen and autodiff like this:
```cmake
cpmaddpackage("https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4…
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PR #11208 extended the `ComputeSignedDistanceToPoint()` for use with AutoDiff scalar. However, the code that provides correct answers when the scalar is double produces garbage derivatives of those sa…
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Hello,
I saw that there is a documented `hessian` driver for the reverse mode. And as I checked through the forward eigen header I found the counterpart. However, I cannot get it to work. My exampl…
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The following minimal example produces a stack overflow:
```
// C++ includes
#include
// autodiff include
#include
#include
using namespace autodiff;
// The scalar function for which th…
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### Description
While trying to equip an external sparse linear solver with a JVP rule, I encountered unexpected behavior related to the sparse BCOO matrix. I'm not sure if it's a bug or if I've ov…