Towards physics-based deep learning in OpenFOAM: Combining OpenFOAM with the PyTorch C++ API (Slides)

dc.contributor.author Maric, Tomislav
dc.contributor.author Weiner, Andre
dc.date.accessioned 2022-07-11T17:58:22Z
dc.date.available 2022-07-09T22:51:10Z
dc.date.available 2022-07-11T17:58:22Z
dc.date.created 2022-07-10
dc.date.issued 2022-07-11
dc.description Slides from the Training "Towards physics-based deep learning in OpenFOAM: Combining OpenFOAM with the PyTorch C++ API" given at the 17th OpenFOAM Workshop de_DE
dc.description.version 1.0 de_DE
dc.identifier.uri https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3528.2
dc.identifier.uri https://doi.org/10.48328/tudatalib-913.2
dc.language.iso en de_DE
dc.rights.licenseCC-BY-4.0 (https://creativecommons.org/licenses/by/4.0)
dc.subject machine learning de_DE
dc.subject physics-informed neural networks de_DE
dc.subject computational fluid dynamics de_DE
dc.subject openfoam de_DE
dc.subject.classification 4.22-03
dc.subject.ddc 620
dc.title Towards physics-based deep learning in OpenFOAM: Combining OpenFOAM with the PyTorch C++ API (Slides) de_DE
dc.type Text de_DE
dcterms.accessRights openAccess
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
tuda.history.classification Version=2020-2024;404-03 Strömungsmechanik
tuda.unit TUDa

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