Paper published in a book (Scientific congresses, symposiums and conference proceedings)
Real Time Hyper-elastic Simulations with Probabilistic Deep Learning
DESHPANDE, Saurabh; LENGIEWICZ, Jakub; BORDAS, Stéphane
2022In 15th World Congress on Computational Mechanics (WCCM-XV)
Peer reviewed
 

Files


Full Text
WCCM2022_Saurabh.pdf
Author preprint (58.86 kB)
Download
Annexes
wccm_presentation.mp4
(215.46 MB)
Download

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Bayesian Inference; Deep Learning; Hyperelasticity
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 Hyper-elastic Simulations with Probabilistic Deep Learning
Publication date :
August 2022
Event name :
15th World Congress on Computational Mechanics (WCCM-XV)
Event date :
31-07-2022 to 05-08-2022
Audience :
International
Main work title :
15th World Congress on Computational Mechanics (WCCM-XV)
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
European Projects :
H2020 - 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design
Funders :
CE - Commission Européenne
Available on ORBilu :
since 07 October 2022

Statistics


Number of views
96 (9 by Unilu)
Number of downloads
81 (10 by Unilu)

Bibliography


Similar publications



Sorry the service is unavailable at the moment. Please try again later.
Contact ORBilu