
MS1-09A Learning models for CFD: opportunities and limitations
Contributions in this session:
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(Keynote)
What is machine learning learning? Autoencoders for reduced-order modelling of turbulence.
L. Magri*, D. Kelshaw, N. Doan -
Explainable transfer learning for stable and generalizable data-driven LES
Y. Guan*, A. Chattopadhyay, P. Hassanzadeh -
Using deep learning techniques for solving convection-dominated convection-diffusion equations
D. Frerichs-Mihov*, L. Henning, V. John -
Learning models from single and multiple sources for fluid problems in engineering design and optimization
L. Mainini* -
Improvements for Uncertainty Estimation in Active Learning – Towards Automated Multifidelity Metamodels
H. Pehlivan Solak*, J. Wackers, R. Pellegrini, A. Serani, M. Diez