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dtoolAI: Reproducibility for Deep Learning
13 references·0 citing·45 second hop
dtoolAI: Reproducibility for Deep Learning (2020)dtoolAI: Reproducibility for Deep LearningTowards FAIR principles for research software (2019)Towards FAIR principles for r…Reproducibility and Replicability in Science (2019)Reproducibility and Replicabi…FAIR Computational Workflows (2019)FAIR Computational WorkflowsA Survey on Collecting, Managing, and Analyzing Provenance from Scripts (2019)A Survey on Collecting, Manag…Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers (2018)Reproducible Research and GIS…Reproducibility in Scientific Computing (2018)Reproducibility in Scientific…Meta-assessment of bias in science (2017)Meta-assessment of bias in sc…A review of bioinformatic pipeline frameworks (2016)A review of bioinformatic pip…Estimating the reproducibility of psychological science (2015)Estimating the reproducibilit…Ten Simple Rules for Reproducible Computational Research (2013)Ten Simple Rules for Reproduc…Prospective and Retrospective Provenance Collection in Scientific Workflow Environments (2010)Prospective and Retrospective…The provenance of electronic data (2008)The provenance of electronic …Electronic documents give reproducible research a new meaning (1992)Electronic documents give rep…Why Most Published Research Findings Are False (2005)Conducting Meta-Analyses in R with the metafor Package (2010)Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs (2013)Estimating Psychological Networks and their Accuracy: A Tutorial Paper (2016)Redefine statistical significance (2017)A tutorial on regularized partial correlation networks. (2018)Taverna: a tool for the composition and enactment of bioinformatics workflows (2004)Galaxy: A platform for interactive large-scale genome analysis (2005)Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences (2010)Reproducibility in Science (2014)Good enough practices in scientific computing. (2017)Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension (2021)Snakemake—a scalable bioinformatics workflow engine (2012)The Taverna workflow suite: designing and executing workflows of Web Services on the desktop, web or in the cloud (2013)Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities (2017)snakePipes: facilitating flexible, scalable and integrative epigenomic analysis (2019)Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers (2021)Explaining heterogeneity in meta-analysis: a comparison of methods (1999)Publication and related bias in meta-analysis (2000)Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias (2008)The earth is flat ( p > 0.05): significance thresholds and the crisis of unreplicable research (2017)What meta-analyses reveal about the replicability of psychological research. (2018)Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis (2019)Why Most Published Research Findings Are False (2005)The Logic of Scientific Discovery (2013)Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv (2019)A taxonomy for reproducible and replicable research in environmental modelling (2020)The data science life cycle (2020)Nextflow enables reproducible computational workflows (2017)The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update (2018)Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows (2020)Conceptualising fairness: three pillars for medical algorithms and health equity (2022)Applying the FAIR Principles to computational workflows (2025)BioContainers: an open-source and community-driven framework for software standardization (2017)Bayesian Analysis Reporting Guidelines (2021)A large-scale study on research code quality and execution (2022)An invitation to reproducible computational research (2010)Journal of Computational Neuroscience (2013)Tools and techniques for computational reproducibility (2016)Special Issue: The First Provenance Challenge (2007)A survey on scholarly data: From big data perspective (2017)GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond (2019)Challenges for assessing replicability in preclinical cancer biology (2021)Replicability, Robustness, and Reproducibility in Psychological Science (2021)Prevalence of questionable research practices, research misconduct and their potential explanatory factors: A survey among academic researchers in The Netherlands (2022)
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References

  • 2015Estimating the reproducibility of psychological science8,516 cited
  • 2019Reproducibility and Replicability in Science921 cited
  • 2013Ten Simple Rules for Reproducible Computational Research875 cited
  • 2017Meta-assessment of bias in science364 cited
  • 2019Towards FAIR principles for research software322 cited
  • 2016A review of bioinformatic pipeline frameworks250 cited
  • 2008The provenance of electronic data224 cited
  • 1992Electronic documents give reproducible research a new meaning212 cited
  • 2019FAIR Computational Workflows171 cited
  • 2018Reproducibility in Scientific Computing149 cited
  • 2018Reproducible Research and GIScience: An Evaluation Using GIScience Conference Papers136 cited
  • 2010Prospective and Retrospective Provenance Collection in Scientific Workflow Environments72 cited
  • 2019A Survey on Collecting, Managing, and Analyzing Provenance from Scripts47 cited

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