From 62f210500538d1387be0451d437b9bd01fd286f8 Mon Sep 17 00:00:00 2001 From: aloctavodia Date: Fri, 7 Feb 2025 15:35:52 +0200 Subject: [PATCH] update arviz --- 2025/ideas-list.md | 3 ++- README.md | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/2025/ideas-list.md b/2025/ideas-list.md index d679ead7..1fe10d8b 100644 --- a/2025/ideas-list.md +++ b/2025/ideas-list.md @@ -4,7 +4,8 @@ This is the home page of projects ideas of NumFOCUS for Google Summer of Code 20 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. - +- [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 4d05f698..7afd8176 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