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 |
Modeling category-selective cortical regions with topographic variational autoencoders TA Keller, Q Gao, M Welling arXiv preprint arXiv:2110.13911, 2021 | 15 | 2021 |
Graph Neural Networks for the Prediction of Molecular Structure–Property Relationships JG Rittig, Q Gao, M Dahmen, A Mitsos, AM Schweidtmann | 13 | 2023 |
Flowsheet recognition using deep convolutional neural networks LS Balhorn, Q Gao, D Goldstein, AM Schweidtmann Computer Aided Chemical Engineering 49, 1567-1572, 2022 | 6 | 2022 |
Transfer learning for process design with reinforcement learning Q Gao, H Yang, SM Shanbhag, AM Schweidtmann Computer Aided Chemical Engineering 52, 2005-2010, 2023 | 5 | 2023 |
Deep reinforcement learning for process design: Review and perspective Q Gao, AM Schweidtmann Current Opinion in Chemical Engineering 44, 101012, 2024 | 4 | 2024 |
MachineLearnAthon: An Action-Oriented Machine Learning Didactic Concept M Tkáč, J Sieber, L Kuhlmann, M Brueggenolte, A Rinciog, M Henke, ... arXiv preprint arXiv:2401.16291, 2024 | | 2024 |
Flowsheet Synthesis through Graph-Based Reinforcement Learning RJ Leenhouts, L Stops, SM Shanbhag, Q Gao, AM Schweidtmann 2022 AIChE Annual Meeting, 2022 | | 2022 |