| Flowsheet generation through hierarchical reinforcement learning and graph neural networks L Stops, R Leenhouts, Q Gao, AM Schweidtmann AIChE Journal 69 (1), e17938, 2023 | 20* | 2023 |
| Graph neural networks for molecular mixture properties R Leenhouts, W Green, F Vermeire AI4bio, Location: Delft, 2024 | | 2024 |
| SolProp: predicting solid solubility of organic solutes for a wide range of conditions using machine learning and thermodynamics R Leenhouts, N Morgan, Y Chung, WH Green, F Vermeire 6th Machine Learning and AI in Bio (Chemical) Engineering Conference, Date …, 2023 | | 2023 |
| Flowsheet Synthesis through Graph-Based Reinforcement Learning RJ Leenhouts, L Stops, SM Shanbhag, Q Gao, AM Schweidtmann 2022 AIChE Annual Meeting, 2022 | | 2022 |
| Replication Data for: Property Prediction of Fuel Mixtures using Pooled Graph Neural Networks R LEENHOUTS, T Larsson KU Leuven RDR, 0 | | |
Qinghe GaoDelft university of technology在 tudelft.nl 的电子邮件经过验证
Qinghe GaoDelft university of technology在 tudelft.nl 的电子邮件经过验证
Artur M. SchweidtmannDelft University of Technology, Department of Chemical Engineering在 tudelft.nl 的电子邮件经过验证
Laura StopsTechnische Universität München (TUM)在 tum.de 的电子邮件经过验证