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Other literature type . 2024
License: CC BY
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Presentation . 2024
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2024
License: CC BY
Data sources: Datacite
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Digital Twin Engine for Science: an ML Workflow perspective

Authors: Sarma, Rakesh; Rüttgers, Mario; Bunino, Matteo; Lintermann, Andreas;

Digital Twin Engine for Science: an ML Workflow perspective

Abstract

This presentation provides an overview on the ML workflow approach adopted in the interTwin project. Initially an introduction to the project is provided, followed by the details on the itwinai library, example of an integration of a use-case, and finally some conclusions are drawn and relevant links are provided. The presentation was part of an internal seminar at the Institut für Energie- und Klimaforschung (IEK) at Forschingszentrum Jülich.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Related to Research communities
EGI : advanced computing for research