4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CE2022★ 4 cited
Computational reproducibility of Jupyter notebooks from biomedical publications
Sheeba Samuel, Daniel Mietchen
Jupyter notebooks allow to bundle executable code with its documentation and output in one interactive environment, and they represent a popular mechanism to document and share com…
cs.LG2020★ 1 cited
Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles
Sheeba Samuel, Frank Löffler, Birgitta König-Ries
Machine learning (ML) is an increasingly important scientific tool supporting decision making and knowledge generation in numerous fields. With this, it also becomes more and more…
cs.CY2020
ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks
Sheeba Samuel, Birgitta König-Ries
Computational notebooks have gained widespread adoption among researchers from academia and industry as they support reproducible science. These notebooks allow users to combine co…