Scheduled presentations:

• Keynote Deep Learning-based Reduced Order Modeling for Unsteady Flow and Fluid-Structure Interaction
  *R. Jaiman (University of British Columbia Vancouver), R. Gao (University of British Columbia Vancouver)
• Assessment of Convolutional Recurrent Autoencoder Network for Learning Wave Propagation
  *W. Mallik (University of Glasgow), R. Jaiman (The University of British Columbia), J. Jelovica (The University of British Columbia)
• Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics
  M. Lino (Imperial College London), S. Fotiadis (Imperial College London), A. Bharath (Imperial College London), *C. Cantwell (Imperial College London)
• Graph Neural Networks to Learn Mesh-Based Fluid Simulations with Physical Symmetries
  *M. Horie (RICOS Co. Ltd., University of Tsukuba), N. Mitsume (University of Tsukuba)
• Student Data-driven spectral modeling for the (thermal) quasi-geostrophic equations
  *S. Ephrati (University of Twente), E. Luesink (University of Twente), P. Cifani (University of Twente), A. Franken (University of Twente), B. Geurts (University of Twente)