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Integrated Reproducibility with Self-describing Machine Learning Models
12 references·0 citing·44 second hop
Integrated Reproducibility with Self-describing Machine Learning Models (2023)Integrated Reproducibility with Self-desc…ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks (2021)ReproduceMeGit: A Visualizati…LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems (2021)LIMA: Fine-grained Lineage Tr…dtoolAI: Reproducibility for Deep Learning (2020)dtoolAI: Reproducibility for …Advancing Computational Reproducibility in the Dataverse Data Repository Platform (2020)Advancing Computational Repro…containerit: Generating Dockerfiles for reproducible research with R (2019)containerit: Generating Docke…State of the Art: Reproducibility in Artificial Intelligence (2018)State of the Art: Reproducibi…DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments (2018)DeepDIVA: A Highly-Functional…ReproZip (2016)ReproZip1,500 scientists lift the lid on reproducibility (2016)1,500 scientists lift the lid…RDataTracker and DDG Explorer (2015)RDataTracker and DDG ExplorernoWorkflow: Capturing and Analyzing Provenance of Scripts (2015)noWorkflow: Capturing and Ana…Using automatic persistent memoization to facilitate data analysis scripting (2011)Using automatic persistent me…Querying and re-using workflows with VsTrails (2008)A Quick Guide to Organizing Computational Biology Projects (2009)Instrumentation and Trace Analysis for Ad-Hoc Python Workflows in Cloud Environments (2015)Using Introspection to Collect Provenance in R (2018)SciInc: A Container Runtime for Incremental Recomputation (2019)Provenance and scientific workflows (2008)Reproducible research in signal processing (2009)How scientists fool themselves – and how they can stop (2015)The Sacred Infrastructure for Computational Research (2017)Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv (2019)Reproducibility in machine‐learning‐based research: Overview, barriers, and drivers (2025)Provenance for Computational Tasks: A Survey (2008)YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts (2015)Sustainable computational science: the ReScience initiative (2017)Believe it or not: how much can we rely on published data on potential drug targets? (2011)Reproducible Research in Computational Science (2011)Redefine statistical significance (2017)Threats of a replication crisis in empirical computer science (2020)Applications of deep learning in stock market prediction: Recent progress (2021)Reproducibility in machine learning for health research: Still a ways to go (2021)Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling (2012)Six red flags for suspect work (2013)Evaluating replicability of laboratory experiments in economics (2016)Mapping platforms into a new open science model for machine learning (2019)Statistical Analyses and Reproducible Research (2007)An introduction to Docker for reproducible research (2015)Singularity: Scientific containers for mobility of compute (2017)Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research (2020)A Framework for Moving Beyond Computational Reproducibility: Lessons from Three Reproductions of Geographical Analyses of COVID‐19 (2023)Reproducible Research Practices and Barriers to Reproducible Research in Geography: Insights from a Survey (2023)Jupyter Notebooks – a publishing format for reproducible computational workflows (2016)Binder 2.0 - Reproducible, interactive, sharable environments for science at scale (2018)Reproducibility and Replicability in Science (2019)Nine best practices for research software registries and repositories (2022)Reproducibility as a service (2023)Reproducible research policies and software/data management in scientific computing journals: a survey, discussion, and perspectives (2025)Ten Simple Rules for Reproducible Computational Research (2013)Estimating the reproducibility of psychological science (2015)Scientific workflow management and the Kepler system (2005)VisTrails (2006)Incremental knowledge base construction using DeepDive (2015)A manifesto for reproducible science (2017)Bioconda: sustainable and comprehensive software distribution for the life sciences (2018)The nf-core framework for community-curated bioinformatics pipelines (2020)
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References

  • 20161,500 scientists lift the lid on reproducibility4,200 cited
  • 2018State of the Art: Reproducibility in Artificial Intelligence292 cited
  • 2015noWorkflow: Capturing and Analyzing Provenance of Scripts129 cited
  • 2016ReproZip128 cited
  • 2020dtoolAI: Reproducibility for Deep Learning38 cited
  • 2011Using automatic persistent memoization to facilitate data analysis scripting35 cited
  • 2018DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments32 cited
  • 2021LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems30 cited
  • 2020Advancing Computational Reproducibility in the Dataverse Data Repository Platform25 cited
  • 2019containerit: Generating Dockerfiles for reproducible research with R19 cited
  • 2021ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks13 cited
  • 2015RDataTracker and DDG Explorer10 cited

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