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Unpublished conference/Abstract (Scientific congresses, symposiums and conference proceedings)
Novel deep learning approaches for learning scientific simulations
DESHPANDE, Saurabh
;
SOSA, Raul Ian
;
BORDAS, Stéphane
et al.
2023
•
The 14th International Conference of Computational Methods (ICCM2023)
Peer reviewed
Permalink
https://hdl.handle.net/10993/55478
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Keywords :
Non-linear FEM; Deep learning; Surrogate modeling
Research center :
ULHPC - University of Luxembourg: High Performance Computing
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
DESHPANDE, Saurabh
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
SOSA, Raul Ian
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
BORDAS, Stéphane
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
LENGIEWICZ, Jakub
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
External co-authors :
yes
Language :
English
Title :
Novel deep learning approaches for learning scientific simulations
Publication date :
August 2023
Event name :
The 14th International Conference of Computational Methods (ICCM2023)
Event place :
Ho Chi Minh, Vietnam
Event date :
06-08-2023 to 10-08-2023
Audience :
International
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
European Projects :
H2020 - 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design
Name of the research project :
R-AGR-3325 - H2020-MSCA-ITN-2017-764644-RAINBOW (01/04/2018 - 31/03/2023) - BORDAS Stéphane
Funders :
CE - Commission Européenne [BE]
Union Européenne [BE]
Available on ORBilu :
since 02 July 2023
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