Scheduled presentations:

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