| Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing S Yu, T Nabil Frontiers in Physics 9, 730685, 2021 | 5 | 2021 |
| Towards Optimal District Heating Temperature Control in China with Deep Reinforcement Learning A Le-Coz, T Nabil, F Courtot arXiv preprint arXiv:2012.09508, 2020 | 5 | 2020 |
| Generative Approaches for the Synthesis of Process Structures T Nabil, JM Commenge, T Neveux Computer Aided Chemical Engineering 49, 289-294, 2022 | 3 | 2022 |
| Machine learning based design of a supercritical CO2 concentrating solar power plant T Nabil, Y Le Moullec, A Le Coz, EDFRDC Center 3rd European Conference on Supercritical CO2 (sCO2) Power Systems 2019: 19th …, 2019 | 2 | 2019 |
| Maximum likelihood estimation of a low-order building model T Nabil, E Moulines, F Roueff, JM Jicquel, A Girard 2016 24th European Signal Processing Conference (EUSIPCO), 702-707, 2016 | 2 | 2016 |
| Traitement quantique des langues : état de l’art S Campani, T Nabil, M Bothua Traitement Automatique des Langues 64 (1), 11-35, 2023 | | 2023 |
| Data-driven structural synthesis of supercritical CO2 power cycles T Nabil, M Noaman, T Morosuk Frontiers in Chemical Engineering 5, 1144115, 2023 | | 2023 |
| Identification de modèle thermique de bâtiment dans un environnement d'objets connectés T Nabil Paris, ENST, 2018 | | 2018 |
| Building identification within a connected object ecosystem T Nabil Télécom ParisTech, 2018 | | 2018 |
| Identification of a thermal building model by learning the dynamics of the solar flux T Nabil, F Roueff, JM Jicquel, A Girard 2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017 | | 2017 |
| Méthode de Monte Carlo à dynamique hamiltonienne pour estimation d'un modèle thermique de bâtiment T Nabil, E Moulines, JM Jicquel, A Girard, C Lajaunie XXVIe colloque GRETSI, 2017 | | 2017 |
| On the Modelling of Kainate Receptor Channels TE Nabil | | 2014 |
