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Qinghe Gao
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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
152021
Graph Neural Networks for the Prediction of Molecular Structure–Property Relationships
JG Rittig, Q Gao, M Dahmen, A Mitsos, AM Schweidtmann
132023
Flowsheet recognition using deep convolutional neural networks
LS Balhorn, Q Gao, D Goldstein, AM Schweidtmann
Computer Aided Chemical Engineering 49, 1567-1572, 2022
62022
Transfer learning for process design with reinforcement learning
Q Gao, H Yang, SM Shanbhag, AM Schweidtmann
Computer Aided Chemical Engineering 52, 2005-2010, 2023
52023
Deep reinforcement learning for process design: Review and perspective
Q Gao, AM Schweidtmann
Current Opinion in Chemical Engineering 44, 101012, 2024
42024
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
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Articles 1–8