| Machine learning in chemical product engineering: The state of the art and a guide for newcomers C Trinh, D Meimaroglou, S Hoppe Processes 9 (8), 1456, 2021 | 34 | 2021 |
| On the Development of Descriptor-Based Machine Learning Models for Thermodynamic Properties: Part 1—From Data Collection to Model Construction: Understanding of the Methods … C Trinh, Y Tbatou, S Lasala, O Herbinet, D Meimaroglou Processes 11 (12), 3325, 2023 | 3 | 2023 |
| Machine Learning for the prediction of the thermochemical properties (enthalpy and entropy of formation) of a molecule from its molecular descriptors C Trinh, D Meimaroglou, S Lasala, O Herbinet Computer Aided Chemical Engineering 51, 1471-1476, 2022 | 2 | 2022 |
| On the Development of Descriptor-Based Machine Learning Models for Thermodynamic Properties: Part 2—Applicability Domain and Outliers C Trinh, S Lasala, O Herbinet, D Meimaroglou Algorithms 16 (12), 573, 2023 | 1 | 2023 |
| A Comprehensive Study on the Styrene–GTR Radical Graft Polymerization: Combination of an Experimental Approach, on Different Scales, with Machine Learning Modeling C Trinh, S Hoppe, R Lainé, D Meimaroglou Macromol 3 (1), 79-107, 2023 | | 2023 |
| 17e Journées Scientifiques C Trinh, B Lamari, D Meimaroglou, S Hoppe | | |
