Scheduled presentations:

• Keynote Machine Learning for Enhancing and Complementing CFD Simulations: Potentials and Limitations for Industrial Applications
  *P. Bekemeyer (DLR), S. Görtz (DLR), A. Krumbein (DLR), C. Grabe (DLR)
• Learning Six Degree-of-Freedom Ship Motion in Random Seas with Multi-Fidelity Data
  *K. Maki (University of Michigan), K. Marlantes (University of Michigan), K. Silva (University of Michigan)
• Leveraging Differentiable Physics to Efficiently Learn Flow Past Arbitrary Geometries
  *S. Brahmachary (Technical University of Munich), N. Thuerey (Technical University of Munich)
• Improvements for Uncertainty Estimation in Active Learning – Towards Automated Multifidelity Metamodels
  *H. Pehlivan Solak (LHEEA, Research Laboratory in Hydrodynamics, Energetics and Atmospheric Environment), J. Wackers (LHEEA, Research Laboratory in Hydrodynamics, Energetics and Atmospheric Environment), R. Pellegrini (CNR-INM, National Research Council-Institute of Marine Engineering), A. Serani (CNR-INM, National Research Council-Institute of Marine Engineering), M. Diez (CNR-INM, National Research Council-Institute of Marine Engineering)