46 citations · 70 across the 13 of their papers we have counts for
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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…