Real-Time Large Deformation Simulations Using Probabilistic Deep Learning Framework

DESHPANDE, Saurabh; LENGIEWICZ, Jakub; BORDAS, Stéphane

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Poster (Scientific congresses, symposiums and conference proceedings)

Real-Time Large Deformation Simulations Using Probabilistic Deep Learning Framework

DESHPANDE, Saurabh; LENGIEWICZ, Jakub; BORDAS, Stéphane

2022 • The Platform for Advanced Scientific Computing (PASC) Conference

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https://hdl.handle.net/10993/52829

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Keywords :

Bayesian Deep learning; Finite Element method; real time simulation

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 :

Real-Time Large Deformation Simulations Using Probabilistic Deep Learning Framework

Publication date :

28 June 2022

Event name :

The Platform for Advanced Scientific Computing (PASC) Conference

Event date :

27-06-2022 to 28-06-2022

Audience :

International

Focus Area :

Computational Sciences

Additional URL :

https://pasc22.pasc-conference.org/program/schedule/index.html%3Fpost_type=page&p=10&id=pos122&sess=sess181.html

European Projects :

H2020 - 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design

Funders :

CE - Commission Européenne
European Union

Available on ORBilu :

since 20 November 2022

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