-
Updated
Dec 30, 2021
probabilistic-programming
Here are 368 public repositories matching this topic...
-
Updated
Feb 21, 2022 - Python
-
Updated
Oct 22, 2019 - Jupyter Notebook
-
Updated
Feb 17, 2022 - Python
Are there any plans to add a Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) to TFP? Those are usually very common distributions in other packages, and it shouldn't be hard to implement.
-
Updated
Jan 9, 2020 - Python
Ankit Shah and I are trying to use Gen to support a project and would love the addition of a dirichlet distribution
-
Updated
Jul 26, 2021 - Jupyter Notebook
-
Updated
Feb 21, 2022 - Julia
-
Updated
Mar 15, 2021 - Go
Dear Numpyro developers,
Please develop Euler Maruyama features in numpyro similar to features found in PyMC.
Thanks alot.
-
Updated
Feb 18, 2022 - Python
-
Updated
Feb 17, 2021 - Python
-
Updated
Aug 7, 2020 - Python
-
Updated
Feb 8, 2022
-
Updated
Feb 21, 2022 - Python
-
Updated
Jan 17, 2020 - Swift
-
Updated
Aug 13, 2021 - Jupyter Notebook
-
Updated
Oct 2, 2020 - JavaScript
The current example on MDN from Edward tutorials needs small modifications to run on edward2. Documentation covering these modifications will be appreciated.
-
Updated
Feb 16, 2022 - Julia
Hi,
Looks like there is support for lots of common distribution. There are a handful of other distributions which are not presently supported but could (fingers crossed) be easily implemented. Looking at [Stan's Function Reference] I see...
- Beta Binomial
- [Chi-Square](https://mc-stan.org/docs/2
Improve tests
There are a variety of interesting optimisations that can be performed on kernels of the form
k(x, z) = w_1 * k_1(x, z) + w_2 * k_2(x, z) + ... + w_L k_L(x, z)A naive recursive implementation in terms of the current Sum and Scaled kernels hides opportunities for parallelism in the computation of each term, and the summation over terms.
Notable examples of kernels with th
GPU Support
-
Updated
Nov 2, 2020 - Haskell
Rather than trying to rebuild all functionality from Distributions.jl, we're first focusing on reimplementing logdensity (logpdf in Distributions), and delegating most other functions to the current Distributions implementations.
So for example, we have
distproxy(d::Normal{(:μ, :σ)}) = Dists.Normal(d.μ, d.σ)This makes some functions in Distributions.jl available through
-
Updated
Sep 12, 2019 - Scala
We need to add a static analysis tool that triggers on each PR and provides a report, ideally flake8 style where we can configure its behaviour and have the action fail until the PR respects all imposed rules. The "configure behaviour" bit is important since we might have some standards that are not in line with static analysis preferences (e.g. there's certain bits where we use exec and `ev
-
Updated
Nov 18, 2021 - JavaScript
Improve this page
Add a description, image, and links to the probabilistic-programming topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the probabilistic-programming topic, visit your repo's landing page and select "manage topics."
The introduction page in Cell 23 has contour plots showing the cross sections of Posterior.
The legend does not have the appropriate patches to help distinguish between the two guides (SVI Diagonal Normal and SVI MV Normal)
I thi