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Poster (Scientific congresses, symposiums and conference proceedings)
Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations
DESHPANDE, Saurabh
;
LENGIEWICZ, Jakub
;
BORDAS, Stéphane
2023
•
The Platform for Advanced Scientific Computing (PASC) Conference 2023
Peer reviewed
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https://hdl.handle.net/10993/55643
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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)
LENGIEWICZ, Jakub
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
BORDAS, Stéphane
;
University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
External co-authors :
yes
Language :
English
Title :
Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations
Publication date :
27 June 2023
Event name :
The Platform for Advanced Scientific Computing (PASC) Conference 2023
Event date :
26-06-2023 to 28-06-2023
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
Union Européenne
Available on ORBilu :
since 20 July 2023
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