Reproducibility package for "Discovering Generative Models from Event Logs: Data-driven Simulation vs Deep Learning"

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dc.contributor.authorManuel Camargo
dc.contributor.authorMarlon Dumas
dc.contributor.authorOscar González-Rojas
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T18:36:58Z
dc.date.available2026-03-22T18:36:58Z
dc.date.issued2020
dc.description.abstractData and generative models for research article <em>Discovering Generative Models from Event Logs: Data-driven Simulation vs Deep Learning</em>. This record contains the complete and partitioned event logs, deep learning generative models (*.h5 format), simulation models for the BIMP simulator (*.bpmn format), and all the raw and summarized results of the paper. The source code of the project can be found at https://github.com/AdaptiveBProcess/DDSvsDL
dc.identifier.doi10.5281/zenodo.4264885
dc.identifier.urihttps://doi.org/10.5281/zenodo.4264885
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/71168
dc.language.isoen
dc.publisherEuropean Organization for Nuclear Research
dc.relation.ispartofZenodo (CERN European Organization for Nuclear Research)
dc.sourceUniversity of Tartu
dc.subjectComputer science
dc.subjectGenerative model
dc.subjectEvent (particle physics)
dc.subjectReproducibility
dc.subjectArtificial intelligence
dc.subjectGenerative grammar
dc.subjectDeep learning
dc.subjectMachine learning
dc.subjectData science
dc.subjectNatural language processing
dc.titleReproducibility package for "Discovering Generative Models from Event Logs: Data-driven Simulation vs Deep Learning"
dc.typearticle

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