Capturing end-to-end provenance for machine learning pipelines

2025/07/01 by Marius Schlegel, Kai-Uwe Sattler · 18 citations

paper · doi:10.1016/j.is.2024.102495

published in Information Systems 132, 102495 (Elsevier BV)

crossref created 2024/12/21 · crossref issued 2025/07/01 · crossref published 2025/07/01 · crossref published-print 2025/07/01 · crossref deposited 2025/11/04 · crossref indexed 2026/08/07

Citations

• Management of Machine Learning Lifecycle Artifacts: A Survey
• Management of Machine Learning Lifecycle Artifacts
• Packaging research artefacts with RO-Crate
• Workflow Provenance in the Lifecycle of Scientific Machine Learning
• Vamsa: Automated Provenance Tracking in Data Science Scripts
• Advances and Open Problems in Federated Learning
• OpenML
• Modeling wine preferences by data mining from physicochemical properties