An integrated analysis platform for efficiently achieving computational reproducibility
-
Updated
Nov 15, 2022 - Python
An integrated analysis platform for efficiently achieving computational reproducibility
Distributed integrity infrastructure for collusion-resistant independent verification. Blind peer validation of any verifiable claim — scientific, regulatory, or institutional — recorded as tamper-evident Harmony Records. Built in Rust on Holochain.
A structured guide to computational reproducibility reviews
Teaching computational reproducibility for neuroimaging
Eindhoven University of Technology (TU/e) course "Improving Your Statistical Questions" by Daniël Lakens on Coursera (completed Dec 2022).
Dockerfile to build an image for use in the repliCATS pipeline
Gemelo Digital para Simulación Sanitaria: Impacto de la Promoción y Prevención (PyP) en la demanda y costos.
Repository for the "Computational Reproducibility in Machine Learning" workshop, containing a setup guide, slides, and files to support hands-on reproducibility exercises.
This repository contains the short talk "Computational Reproducibility & Docker" given by Ross Gayler to the ReproducibiliTea Melbourne group on 2026-03-26. The target paper is “Longitudinal Study of the Software Environments Produced by Dockerfiles from Research Artifacts: Initial Design” (Guilloteau et al., 2025, DOI:10.1145/3736731.3746146)
2019 Computational Reproducibility Workshop Series, led by Nelle Varoquaux
Six-phase harness that verifies a statistical analysis is internally consistent, reproducible, and agrees with an independent R implementation
Scripts and files related to my Master's thesis.
Reference implementation of MicrobiomeRiskScore (MRS): a treatment-aware Transformer that predicts healthcare-associated infections from longitudinal gut microbiome dynamics. Companion code to Ma et al., npj Digital Medicine.
Add a description, image, and links to the computational-reproducibility topic page so that developers can more easily learn about it.
To associate your repository with the computational-reproducibility topic, visit your repo's landing page and select "manage topics."