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Number of visits: 40294


13:00 - 15:00

Technical sessions
MS06 - Reduced Order Modelling

Invited Session organized by Trond Kvamsdal

MoA02I

Room: Room1

Chair: Trond Kvamsdal

Machine learning powered nonlinear manifold reduced order model

Y. Kim, Y.  Choi, D. Widemann and T. Zohdi

Abstract

Machine learning for nonlinear model order reduction.

T. Daniel, F. Casenave, N. Akkari and D. Ryckelynck

Abstract

From linear mappings to deep learning for model order reduction of numerical simulations of industrial interest

R. Bravo, C. Roig, R. Rossi and J Hernandez

Abstract

Data-driven reduced order modeling for CFD stochastic time-dependent problems

A. Abdedou and A. Soulaļmani

Abstract

A hybrid POD-Galerkin approach for turbulent flow problems

V. Tsiolakis, T. Kvamsdal, A. Rasheed, E. Fonn and H. Van Brummelen

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