From 56b6f6c5ee8e1c45887365763d9305e0341aa90d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cl=C3=A9lia=20de=20Mulatier?= Date: Fri, 5 Jun 2026 17:26:10 +0200 Subject: [PATCH 1/4] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 4f5f8eb..510b7c2 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ The best MCM for a given dataset is found by optimising the marginal likelihood The package can be used to analyse datasets with **up to n = 128 random variables** and is limited to **variables that can take up to q=10 different values** (though it was extensively tested only up to q=5). [1] *Bayesian inference of minimally complex models with interactions of arbitrary order*, C. de Mulatier and M. Marsili, [Phys. Rev. E 111, 054307](https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.054307) ([arXiv:2008.00520](https://arxiv.org/abs/2008.00520))
-[2] *Modeling higher-order interactions in discrete data with maximum entropy models*, A. De Clercq, M. Moody and C. de Mulatier, arxiv (coming soon) +[2] *Modeling Discrete Data with High-Order Vector Potts Models*, A. De Clercq, M. Moody and C. de Mulatier, [arXiv:2606.03429](https://arxiv.org/abs/2606.03429) ## General information From a57044404aa8360d997cf6af221595d3eb29b104 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cl=C3=A9lia=20de=20Mulatier?= Date: Mon, 8 Jun 2026 20:34:01 +0200 Subject: [PATCH 2/4] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 510b7c2..af7503f 100644 --- a/README.md +++ b/README.md @@ -51,7 +51,7 @@ C++11, Python (version 3.11 or above) **Installation:** using CMake (version 3.26.4) or using Docker ## To cite this repository -A. De Clercq, C. de Mulatier (2025). *MinCompSpin: Python package for analyzing discrete datasets with minimally complex models*. Zenodo. https://github.com/DM-Lab-UvA/MinCompSpin. +A. De Clercq, C. de Mulatier (2026). *MinCompSpin (mcmpy): a package for modeling discrete datasets with minimally complex models*. Zenodo. DOI [10.5281/zenodo.20490992](https://doi.org/10.5281/zenodo.20490992). ## Related previous repositories From e18600e60e548b899ba198d54bc457fe26d1f663 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cl=C3=A9lia=20de=20Mulatier?= Date: Mon, 8 Jun 2026 20:38:53 +0200 Subject: [PATCH 3/4] Update README.md --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index af7503f..4fd535b 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # MinCompSpin (`mcmpy`) +[![DOI](https://zenodo.org/badge/950501216.svg)](https://doi.org/10.5281/zenodo.20490992) + MinCompSpin is a C++ library with Python bindings for analyzing discrete datasets using Minimally Complex Models (MCMs). Once compiled, it creates the Python package `mcmpy`. MCMs are a family of maximum entropy models (known as spin models) that have interactions of arbitrarily high order grouped in a community-like structure. Compared to other spin models, they have minimal information-theoretic complexity. From 96ff7330fee0fc55a6f7e4bd0591a468a5ef8067 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Cl=C3=A9lia=20de=20Mulatier?= Date: Mon, 8 Jun 2026 21:20:31 +0200 Subject: [PATCH 4/4] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 4fd535b..a88f55f 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,7 @@ # MinCompSpin (`mcmpy`) -[![DOI](https://zenodo.org/badge/950501216.svg)](https://doi.org/10.5281/zenodo.20490992) +[![DOI](https://img.shields.io/badge/DOI-10.5281%2Fzenodo.20490992-blue)](https://doi.org/10.5281/zenodo.20490992) +[![docs](https://img.shields.io/badge/docs-dm--lab--uva.github.io-brightgreen)](https://dm-lab-uva.github.io/MinCompSpin/index.html) MinCompSpin is a C++ library with Python bindings for analyzing discrete datasets using Minimally Complex Models (MCMs). Once compiled, it creates the Python package `mcmpy`.