| MLGCN: Multi-Laplacian graph convolutional networks for human action recognition A Mazari, H Sahbi The British machine vision conference (BMVC), 2019 | 41 | 2019 |
| AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions F Bonnet, JA Mazari, P Cinnella Thirty-sixth Conference on Neural Information Processing Systems Datasets …, 2022 | 33 | 2022 |
| Deep temporal pyramid design for action recognition A Mazari, H Sahbi ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 20 | 2019 |
| An extensible benchmarking graph-mesh dataset for studying steady-state incompressible Navier-Stokes equations F Bonnet, JA Mazari, T Munzer, P Yser, P Gallinari ICLR2022, 2022 | 11 | 2022 |
| Multi-scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators L Migus, Y Yin, JA Mazari, P Gallinari ICLR2022, 2022 | 8 | 2022 |
| Coarse-to-fine aggregation for cross-granularity action recognition A Mazari, H Sahbi 2020 IEEE International Conference on Image Processing (ICIP), 1541-1545, 2020 | 8 | 2020 |
| Byzantine fault tolerance in distributed machine learning: a survey D Bouhata, H Moumen, JA Mazari, A Bounceur arXiv preprint arXiv:2205.02572, 2022 | 7 | 2022 |
| Human action recognition with multi-laplacian graph convolutional networks A Mazari, H Sahbi arXiv preprint arXiv:1910.06934, 2019 | 5 | 2019 |
| Infinity: Neural field modeling for reynolds-averaged navier-stokes equations L Serrano, L Migus, Y Yin, JA Mazari, P Gallinari arXiv preprint arXiv:2307.13538, 2023 | 3 | 2023 |
| Human action recognition with deep temporal pyramids A Mazari, H Sahbi arXiv preprint arXiv:1905.00745, 2019 | 2 | 2019 |
| Deep Learning for Action Recognition in Videos (Thesis) A Mazari Sorbonne Université, 2020 | 1 | 2020 |
| ML4PhySim: Machine Learning for Physical Simulations Challenge (The airfoil design) M Yagoubi, M Leyli-Abadi, D Danan, JP Brunet, JA Mazari, F Bonnet, ... arXiv preprint arXiv:2403.01623, 2024 | | 2024 |
| Deep multiple aggregation networks for action recognition A Mazari, H Sahbi International Journal of Multimedia Information Retrieval 13 (1), 9, 2024 | | 2024 |
| Multi-Objective Hull Form Optimization with CAD Engine-based Deep Learning Physics for 3D Flow Prediction JA Mazari, A Reverberi, P Yser, S Sigmund arXiv preprint arXiv:2306.12915, 2023 | | 2023 |
| Apprentissage profond pour la reconnaissance d’actions en vidéos A Mazari Sorbonne université, 2020 | | 2020 |
| Action Recognition with Deep Multiple Aggregation Networks A Mazari, H Sahbi arXiv preprint arXiv:2006.04489, 2020 | | 2020 |
| Deep hierarchical pooling design for cross-granularity action recognition A Mazari, H Sahbi arXiv preprint arXiv:2006.04473, 2020 | | 2020 |
| Research Collaborations : A guide for early career researchers by early career researchers (The University of Edinburgh - Scotland. LERU 2019) A Mazari https://www.leru.org/files/News/Research-Collaborations-A-guide-for-early …, 2019 | | 2019 |
| Supplementary Material : MULTI-LAPLACIAN GCN FOR HUMAN ACTION RECOGNITION HS Ahmed Mazari https://bmvc2019.org/wp-content/uploads/papers/1103-supplementary.pdf, 0 | | |
Hichem SahbiCNRS Sorbonne UniversityVerified email at lip6.fr
