AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions. - Florent Bonnet; Jocelyn Ahmed Mazari; Paola Cinnella; Patrick Gallinari (NeurIPS, 2022)

Multi-Scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators. - Léon Migus; Yuan Yin; Jocelyn Ahmed Mazari; Patrick Gallinari (TAG-ML, 2022)

An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations. - Florent Bonnet; Jocelyn Ahmed Mazari; Thibaut Munzer; Pierre Yser; Patrick Gallinari (CoRR, 2022)

Multi-Objective Hull Form Optimization with CAD Engine-based Deep Learning Physics for 3D Flow Prediction. - Jocelyn Ahmed Mazari; Antoine Reverberi; Pierre Yser; Sebastian Sigmund (CoRR, 2023)

INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations. - Louis Serrano; Léon Migus; Yuan Yin; Jocelyn Ahmed Mazari; Patrick Gallinari (CoRR, 2023)

ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design). - Mouadh Yagoubi; Milad Leyli-Abadi; David Danan; Jean-Patrick Brunet; Jocelyn Ahmed Mazari; Florent Bonnet; Asma Farjallah; Marc Schoenauer; Patrick Gallinari (CoRR, 2024)

NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design. - Mouadh Yagoubi; David Danan; Milad Leyli-Abadi; Jean-Patrick Brunet; Jocelyn Ahmed Mazari; Florent Bonnet; Maroua Gmati; Asma Farjallah; Paola Cinnella; Patrick Gallinari; Marc Schoenauer (CoRR, 2024)

NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis. - Mouadh Yagoubi; David Danan; Milad Leyli-Abadi; Jocelyn Ahmed Mazari; Jean-Patrick Brunet; Abbas Kabalan; Fabien Casenave; Yuxin Ma; Giovanni Catalani; Jean Fesquet; Jacob Helwig; Xuan Zhang; et al. (CoRR, 2025)