diff --git a/2025/ideas-list.md b/2025/ideas-list.md index 3a7a7882..87bf5c0e 100644 --- a/2025/ideas-list.md +++ b/2025/ideas-list.md @@ -5,6 +5,8 @@ Since NumFOCUS is an umbrella organization you will only find links to the ideas page of each organization under the NumFOCUS umbrella at this page. - [aeon](https://github.com/aeon-toolkit/aeon-admin/blob/main/gsoc/gsoc-2025-projects.md) +- [ArviZ](https://github.com/arviz-devs/arviz/wiki/GsoC-2025-projects) - [Data Retriever](https://github.com/weecology/retriever/wiki/GSoC-2025-Project-Ideas) + See the [README](https://github.com/numfocus/gsoc/blob/master/README.md#organizations-confirmed-under-numfocus-umbrella) for contact information of each org. diff --git a/README.md b/README.md index 25357fec..bf390336 100644 --- a/README.md +++ b/README.md @@ -109,7 +109,7 @@ In alphabetic order. ArviZ is a project dedicated to promoting and building tools for exploratory analysis of Bayesian models. It currently has a Python and a Julia interface. ArviZ aims to integrate seamlessly with established probabilistic programming languages like PyStan, PyMC, Turing, Soss, emcee, or Pyro. Where the probabilistic programming languages aim to make it easy to build and solve Bayesian models, the ArviZ libraries aim to make it easy to process and analyze the results from those Bayesian models.

- Website | Ideas List | Contact (Gitter) | Source Code + Website | Ideas List | Contact (Gitter) | Source Code