Suivre
Ali Hebbal
Ali Hebbal
Hybrid Intelligence
Adresse e-mail validée de capgemini.com
Titre
Citée par
Citée par
Année
Bayesian optimization using deep Gaussian processes with applications to aerospace system design
A Hebbal, L Brevault, M Balesdent, EG Talbi, N Melab
Optimization and Engineering 22, 321-361, 2021
65*2021
Multi-objective multidisciplinary design optimization approach for partially reusable launch vehicle design
L Brevault, M Balesdent, A Hebbal
Journal of Spacecraft and Rockets 57 (2), 373-390, 2020
362020
Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities, application to aerospace systems
L Brevault, M Balesdent, A Hebbal
Aerospace Science and Technology 107, 106339, 2020
342020
Multi-fidelity modeling with different input domain definitions using deep Gaussian processes
A Hebbal, L Brevault, M Balesdent, EG Talbi, N Melab
Structural and Multidisciplinary Optimization 63, 2267-2288, 2021
242021
Efficient global optimization using deep gaussian processes
A Hebbal, L Brevault, M Balesdent, EG Taibi, N Melab
2018 IEEE Congress on evolutionary computation (CEC), 1-8, 2018
222018
Multi-objective optimization using deep Gaussian processes: application to aerospace vehicle design
A Hebbal, L Brevault, M Balesdent, EG Talbi, N Melab
AIAA Scitech 2019 Forum, 1973, 2019
212019
Surrogate model-based multi-objective MDO approach for partially Reusable Launch Vehicle design
L Brevault, M Balesdent, A Hebbal, A Patureau De Mirand
AIAA Scitech 2019 Forum, 0704, 2019
62019
Multi-fidelity modeling using DGPs: Improvements and a generalization to varying input space dimensions
A Hebbal, L Brevault, M Balesdent, EG Talbi, N Melab
52019
Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities
L Brevault, M Balesdent, A Hebbal
arXiv preprint arXiv:2006.16728, 2020
42020
Deep Gaussian process for multi-objective Bayesian optimization
A Hebbal, M Balesdent, L Brevault, N Melab, EG Talbi
Optimization and Engineering 24 (3), 1809-1848, 2023
32023
Deep Gaussian processes for the analysis and optimization of complex systems-application to aerospace system design
A Hebbal
Université de Lille, 2021
32021
Mdo related issues: Multi-objective and mixed continuous/discrete optimization
L Brevault, M Balesdent, J Morio, L Brevault, J Pelamatti, A Hebbal, ...
Aerospace system analysis and optimization in uncertainty, 321-358, 2020
22020
Expendable and reusable launch vehicle design
L Brevault, M Balesdent, J Morio, L Brevault, M Balesdent, A Hebbal
Aerospace System Analysis and Optimization in Uncertainty, 421-476, 2020
12020
Processus gaussiens profonds pour l’analyse et l’optimisation des systèmes complexes: application à la conception des systèmes aérospatiaux
A Hebbal
2021
Multi-Disciplinary Design Multi-Objective Optimization of Aerospace Vehicles using Surrogate Models
A Hebbal, L Brevault, M Balesdent, EG Talbi, N Melab
OLA 2018-International Workshop on Optimization and Learning: Challenges and …, 2018
2018
Efficient Global Optimization using Deep Gaussian Processes
A Hebbal, L Brevault, M Balesdent, EG Talbi, N Melab
Springer Optimization and Its Applications
GWA Means, GH Set, D Cover
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–17