A diamond open-access journal in statistics and machine learning A journal of the French Statistical Society (SFdS) — ISSN 2824-7795
Website · Articles · Author guidelines · Reviewer guidelines · Mastodon
Computo promotes computational and algorithmic contributions in statistics and machine learning that provide insight into which models or methods are most appropriate for a given scientific question. Rather than sticking to classical static publications, Computo leverages literate programming and modern scientific-reporting tools to make every published article fully reproducible: code, data, and narrative live together, and readers can re-run the analysis behind the results.
Computo is a diamond open-access journal: free to read, free to publish in, with peer review handled openly through OpenReview.
- computorg.github.io — source of the journal's website (computo-journal.org), built with Quarto.
- computo-quarto-extension — the Quarto extension defining the Computo article format, used by every submission and by the journal's own build pipeline.
- Submission templates, one per supported language, each a GitHub template repository authors can use to start a new submission:
published-*repositories — one repository per published article (e.g. published-paper-tsne), each containing the reproducible source of that article and its rendered GitHub Pages version.- .github (this repository) — organization-wide defaults: profile README, issue templates, and contribution guidelines shared across all Computo repositories.
If you are an author, start from the template matching your language (R, Python, or Julia) and follow the author guidelines. Reviewers can find the process described in the reviewer guidelines.
- Website: computo-journal.org
- Email: contact@computo-journal.org
- Mastodon: @computo@mathstodon.xyz
- LinkedIn: company/computo-sfds
