Jocelyn Ahmed Mazari

An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations

P. Gallinari, F. Bonnet, Jocelyn Ahmed Mazari, 2022, ArXiv.

AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions

P. Gallinari, P. Cinnella, F. Bonnet, 2022, NeurIPS.

AN EXTENSIBLE BENCHMARKING GRAPH-MESH DATASET FOR STUDYING STEADY-STATE INCOM-PRESSIBLE NAVIER-STOKES EQUATIONS GRAPH-MESH DATASET STUDYING STEADY-STATE INCOMPRESSIBLE NAVIER-STOKES

P. Gallinari, F. Bonnet, Jocelyn Ahmed Mazari, 2022 .

Multi-scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators

P. Gallinari, Yuan Yin, Jocelyn Ahmed Mazari, 2022, ArXiv.

AN EXTENSIBLE BENCHMARKING GRAPH-MESH DATASET FOR STUDYING STEADY-STATE INCOM-PRESSIBLE NAVIER-STOKES EQUATIONS GRAPH-MESH DATASET STUDYING STEADY-STATE INCOMPRESSIBLE NAVIER-STOKES

F. Bonnet, Jocelyn Ahmed Mazari, T. Munzer, 2022 .

INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations

P. Gallinari, Yuan Yin, Jocelyn Ahmed Mazari, 2023, ArXiv.

Multi-Objective Hull Form Optimization with CAD Engine-based Deep Learning Physics for 3D Flow Prediction

S. Sigmund, Jocelyn Ahmed Mazari, P. Yser, 2023, 10th Conference on Computational Methods in Marine Engineering.

Multi-scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators

P. Gallinari, Yuan Yin, Jocelyn Ahmed Mazari, 2022, TAG-ML.