Mechanical models used for training & planning
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Mission
Team Legato aims at building intuitive and interactive platforms for computational mechanics problems which allow the users to interact with their models and hence gain insights into unconventional and counter-intuitive phenomena.
Data driven PhD Studentships available with Pascal J. Loew Head of Design SISTO Armaturen S.A. Luxembourg. Phase field. Machine learning. Fracture. @legato-team https://lnkd.in/e5d4X2M
News
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January 25, 2021
Arif Sinan Uslu: The effect of self-paced neurofeedback on EEG learning: An experimental setup
Machine Learning Seminar presentation Topic: The effect of self-paced neurofeedback on EEG learning: An experimental setup Speaker: Arif Sinan Uslu, FHSE, University of Luxembourg Time: Wednesday, 2021.01.27, 10:00 CET How to join: Please contact Jakub Lengiewicz Abstract: Neurofeedback refers to
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January 17, 2021
Milad Zeraatpisheh: Bayesian neural networks and MC Dropout; ways to measure uncertainty in Deep learning
Machine Learning Seminar presentation Topic: Bayesian neural networks and MC Dropout; ways to measure uncertainty in Deep learning Speaker: Milad Zeraatpisheh, FSTM, University of Luxembourg Time: Wednesday 2021.01.20, 10:00 CET How to join: Please contact Jakub Lengiewicz Abstract: Deep learning
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January 12, 2021
Lars Beex: Unsupervised learning to select modes for reduced-order models of hyperelastoplasticity: application to RVEs
Machine Learning Seminar presentation Topic: A Physics-guided Machine Learning Model Based on Peridynamics Speaker: Dr Lars Beex, FSTM, University of Luxembourg Authors: S. Vijayaraghavan (1; 2), L.A.A.Beex (1), L.Noels (2), and S.P.A.Bordas (1) 1) University of Luxembourg, Ave. de la
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December 14, 2020
Erkan Oterkus: A Physics-guided Machine Learning Model Based on Peridynamics
Machine Learning Seminar presentation Topic: A Physics-guided Machine Learning Model Based on Peridynamics Speaker: Pofessor Erkan Oterkus, PeriDynamics Research Center, University of Strathclyde, Glasgow, UK Time: Wednesday 2020.12.16, 10:00 CET How to join: Please contact Jakub Lengiewicz Abstract: With the
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December 1, 2020
Eleni Koronaki: From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics
Machine Learning Seminar presentation Topic: From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics Speaker: Dr. Eleni Koronaki, University of Luxembourg, Department of Computational Science Time: Wednesday 2020.12.09, 10:00 CET How to join: Please
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