diff --git a/2024/ideas-list.md b/2024/ideas-list.md index 080a0cba..ab722c5d 100644 --- a/2024/ideas-list.md +++ b/2024/ideas-list.md @@ -6,7 +6,7 @@ page of each organization under the NumFOCUS umbrella at this page. - [aeon](https://github.com/aeon-toolkit/aeon-admin/blob/main/gsoc/gsoc-2024-projects.md) - [AiiDA](https://github.com/aiidateam/aiida-core/wiki/GSoC-2024-Projects) -- [ArviZ] +- [ArviZ](https://github.com/arviz-devs/arviz/wiki/GSoC-2024-projects) - [biocommons](https://github.com/orgs/biocommons/projects/8/views/1) - [CB-Geo MPM] - [Colour Science] diff --git a/README.md b/README.md index 24907f85..bd3974a6 100644 --- a/README.md +++ b/README.md @@ -106,10 +106,10 @@ In alphabetic order.
- ArviZ, is a project dedicated to promote and build 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 (3 and 4), Turing, Soss, emcee or Pyro. Where the aim of the probabilistic programming languages is to make it easy to build and solve Bayesian models, the aim of the ArviZ libraries is to make it easy to process and analyze the results from those Bayesian models. + 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