Aims and scope

Computo has been created in the context of a reproducibility crisis in science, which calls for higher standards in the publication of scientific results. Computo aims at promoting computational/algorithmic contributions in statistics and machine learning that provide insight into which models or methods are the most appropriate to address a specific scientific question.

The journal welcomes the following types of contributions:

  • New methods with original stats/ML developments, or numerical studies that illustrate theoretical results in stats/ML;
  • Case studies or surveys on stats/ML methods to address a specific (type of) question in data analysis, neutral comparison studies that provide insight into when, how, and why the compared methods perform well or less well;
  • Software papers to present implementations of stats/ML algorithms or to feature the use of a package/toolbox.

An open journal with reproducible contributions

Computo is free for readers and authors.

The reproducibility of numerical results is a necessary condition for publication in Computo. In particular, submissions must include all necessary data (e.g. via zenodo repositories) and code. For contributions featuring the implementation of methods/algorithms, the quality of the provided code is assessed during the review process. We accept contributions in the form of notebooks (e.g. Rmarkdown, or Jupyter).

The reviews are open, i.e. visible to any reader after acceptance of the contribution. Reviewers may choose to remain anonymous or not.


We rely on Jekyll, BibTeX, the aI-folio Jekyll theme, Rmarkdown, Jupyter-book and we drawn our inspiration from Rescience-C and distill.pub among others.