Novel deep learning approaches for learning scientific simulations

Deshpande, Saurabh; Sosa, Raul Ian; Bordas, Stéphane; Lengiewicz, Jakub

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Unpublished conference/Abstract (Scientific congresses, symposiums and conference proceedings)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

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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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