MS1-09A Learning models for CFD: opportunities and limitations

Wed, 26/04/2023
16:00 - 18:00
Rédaction 2

Contributions in this session:

  • (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