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Hassan Ghraieb
Hassan Ghraieb
Mines Paris - PSL University
Verified email at minesparistech.psl.eu
Title
Cited by
Cited by
Year
Direct shape optimization through deep reinforcement learning
J Viquerat, J Rabault, A Kuhnle, H Ghraieb, A Larcher, E Hachem
Journal of Computational Physics 428, 110080, 2021
1552021
Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows
H Ghraieb, J Viquerat, A Larcher, P Meliga, E Hachem
Physical Review Fluids 6 (5), 053902, 2021
422021
Deep reinforcement learning for the control of conjugate heat transfer
E Hachem, H Ghraieb, J Viquerat, A Larcher, P Meliga
Journal of Computational Physics 436, 110317, 2021
302021
Single-step deep reinforcement learning for two-and three-dimensional optimal shape design
H Ghraieb, J Viquerat, A Larcher, P Meliga, E Hachem
AIP Advances 12 (8), 2022
112022
Optimization and passive flow control using single-step deep reinforcement learning
H Ghraieb, J Viquerat, A Larcher, P Meliga, E Hachem
arXiv preprint arXiv:2006.02979, 2020
62020
Deep reinforcement learning for the control of conjugate heat transfer with application to workpiece cooling
E Hachem, H Ghraieb, J Viquerat, A Larcher, P Meliga
arXiv preprint arXiv:2011.15035, 2020
52020
Reinforcement learning for patient-specific optimal stenting of intracranial aneurysms
E Hachem, P Meliga, A Goetz, PJ Rico, J Viquerat, A Larcher, R Valette, ...
Scientific Reports 13 (1), 7147, 2023
42023
On the coupling of deep reinforcement learning and computational fluid dynamics
H Ghraieb
Université Paris sciences et lettres, 2022
2022
Deep reinforcement learning for fluid mechanics
E Hachem, P Meliga, H Ghraieb, R Nemer, R Valette, J Viquerat, ...
8th European Congress on Computational Methods in Applied Sciences and …, 2022
2022
Sur le Couplage de l˘Apprentissage par Renforcement Profond et de la Mecanique des Fluides Numerique On the Coupling of Deep Reinforcement Learning and Computational Fluid Dynamics
H Ghraieb
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Articles 1–10