Scheduled presentations:

• Turbidity Currents Simulations in Channels with Different Slopes Using ROM-NN Models
  *R. Velho (Federal University of Rio de Janeiro), A. Côrtes (Federal University of Rio de Janeiro), G. Barros (Federal University of Rio de Janeiro), J. Camata (Federal University of Juiz de Fora), G. Guerra (Fluminense Federal University), R. Elias (Federal University of Rio de Janeiro), F. Rochinha (Federal University of Rio de Janeiro), A. Coutinho (Federal University of Rio de Janeiro)
• AI Model to Predict in-situ Relative Permeability of Rock Formation
  S. Zhong (Swansea University), X. Ge (Swansea University), H. Thomas (Swansea University), *C. Li (Swansea University)
• The Role of Provenance Data in Physics Informed Machine Learning
  L. Oliveira (COPPE/UFRJ), D. Pina (COPPE/UFRJ), L. Kunstmann (COPPE/UFRJ), D. Oliveira (IC/UFF), *M. Mattoso (COPPE/UFRJ)
• Implicit Neural Representation For Accurate CFD Flow Field Prediction
  *L. de Vito (MTU Aero Engines), N. Pinnau (Microsoft), S. Dey (LMU)
• A Novel Data-based Strategy for RANS Wall Models Inspired from Dirichlet-to-Neumann Map
  *M. Romanelli (DAAA, ONERA), S. Beneddine (DAAA, ONERA), I. Mary (DAAA, ONERA), H. Beaugendre (Bordeaux INP), M. Bergmann (Inria), D. Sipp (DAAA, ONERA)
• Field-inversion analyses for machine-learning applications of compressible RANS computations in a discontinuous Galerkin framework
  *B. Fanizza (DAAA, ONERA), P. Stefanin Volpiani (DAAA, ONERA), F. Renac (DAAA, ONERA), D. Sipp (DAAA, ONERA)
• A machine learned near-well model in OPM
  *P. von Schultzendorff (Universitetet i Bergen), J. Both (Universitetet i Bergen), J. Nordbotten (Universitetet i Bergen), T. Sandve (NORCE), B. Kane (NORCE), D. Marban (NORCE)