Real-time large deformations: A probabilistic deep learning approach

Reference : Real-time large deformations: A probabilistic deep learning approach


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/52344

Title :	Real-time large deformations: A probabilistic deep learning approach
Language :	English
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) >]
Publication date :	Jun-2022
Main document title :	The 8th European Congress on Computational Methods in Applied Sciences and Engineering
Peer reviewed :	Yes
Event name :	The 8th European Congress on Computational Methods in Applied Sciences and Engineering
Event date :	05-06-2022 to 09-06-2022
Event place (city) :	Oslo
Event country :	Norway
Keywords :	[en] Real Time Simulation ; Probabilistic Deep Learning
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/52344
Framework Programme / European Project :	H2020 ; 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design

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Open access	ECCOMAS22_Saurabh.pdf		Publisher postprint	77.43 kB	View/Open

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