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I am very interested in converting DeepLearning models, that contain the PowerSpherical function (https://github.com/andife/power_spherical) to ONNX.
Currently this fails because of the Dirichlet f…
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### Is your feature request related to a problem? Please describe.
I encountered the need to do in some data analysis scenarios, where you use the Dirichlet distribution as a Bayesian prior and wan…
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## 🚀 Feature
The [Dirichlet-Multinomial distribution](https://en.wikipedia.org/wiki/Dirichlet-multinomial_distribution) is something I need for my research. TensorFlow has this distribution imple…
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I am following the docs to implement a multivariate distribution, however, once defining _rand! I assumed rand would also work, but this turns out not to be the case:
```
julia> _rand!(foo,Array{Floa…
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Nice library!
I'm trying to replace my iterative solver with optimistic, but I'm having trouble getting good results. Here's my [pull request](https://github.com/NeilGirdhar/efax/compare/optimisti…
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Some distributions will likely not work because of the check for parent dims being a superset of the child. For instance,
```python
from pymc_marketing.prior import Prior, UnsupportedShapeError
…
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MWE:
```julia
using Random: randn
using Enzyme: Enzyme
using Turing: Turing
Enzyme.API.runtimeActivity!(true)
Turing.@model function MvDirichletWithManualAccumulation(w, doc)
β ~ Turing…
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### Description
This RFC proposes implement large number of probability distributions. The purpose of this issue is to serve as a tracking issue for implement large number of probability distributi…
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There has been user desire for generating random numbers with respect to other distributions (normal in particular). But we should also consider adding other common distributions (power law, binomial,…
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```python
from jax import hessian
from jax.random import PRNGKey, gamma
key = PRNGKey(1)
hessian_sample = hessian(gamma, argnums=(1,))
# NotImplementedError: Differentiation rule for 'random_ga…