-
It would be very nice to have support for AD in `Base.expm`. I would like to contribute to it, but since I am unfamiliar with the AD architecture in Julia I would appreciate some advice.
For Freche…
tpapp updated
2 years ago
-
## Idea
The matrices representing the systems of equations in Cantera are generally solved using [SUNDIALS]. Newer versions of SUNDIALS have a better interface to integrate with heterogeneous c…
-
Working on Ubuntu 20.04, CUDA 11.7, taichi 1.04.
When running the example descirbed [here](https://github.com/taichi-dev/taichi/blob/56689ad61a7fad8dfd6818ef6be9a6d7e8ac1c85/python/taichi/aot/recor…
-
Hi, developers!
My question is, is there any plan to support Convex.jl here with AD like [cvxpylayers](https://github.com/cvxgrp/cvxpylayers)?
For AD of the solution to (convex) optimization probl…
-
Hi,
Is there a way to implement truncated laplace distribution and use it with NUTS sampler? Truncated PDF is original PDF divided
by `CDF(right) - CDF(left)` right?
Use case:
In the physi…
-
When passing a `target_log_prob_fn` that's not built from TF primitives (and hence doesn't allow for automatic differentiation) to the `HamiltonianMonteCarlo` kernel, is there a way to also pass a cus…
-
On v0.1.25 on OSX, I get the following error when computing gradients from the following jit-compiled function.
```python
import numpy as onp
import jax.numpy as np
from jax import grad, jit
…
-
First, thank you for this package !
I am currently trying out its possibilities.
This includes differentiating through the calculations. In the type specification you always seem to require that …
-
#### Summary:
Allow 3rd-party PDE(partial differential equation) libraries to be used to perform inference that involve PDEs.
#### Description:
The design involves `cmdstan`, `stan`, and `math…
-
AutoEnzyme should probably be specialized and not fall back to DI.
In addition to being slower in some cases, it's been shown to cause errors (even segfaults) when using AutoEnzyme in DI whereas us…