| Neural network aided approximation and parameter inference of non-Markovian models of gene expression Q Jiang, X Fu, S Yan, R Li, W Du, Z Cao, F Qian, R Grima Nature communications 12 (1), 2618, 2021 | 112 | 2021 |
| Local–global modeling and distributed computing framework for nonlinear plant-wide process monitoring with industrial big data Q Jiang, S Yan, H Cheng, X Yan IEEE transactions on neural networks and learning systems 32 (8), 3355-3365, 2020 | 85 | 2020 |
| Data-driven two-dimensional deep correlated representation learning for nonlinear batch process monitoring Q Jiang, S Yan, X Yan, H Yi, F Gao IEEE Transactions on Industrial Informatics 16 (4), 2839-2848, 2019 | 52 | 2019 |
| Design teacher and supervised dual stacked auto-encoders for quality-relevant fault detection in industrial process S Yan, X Yan Applied Soft Computing 81, 105526, 2019 | 46 | 2019 |
| Using Labeled Autoencoder to Supervise Neural Network Combined with k-Nearest Neighbor for Visual Industrial Process Monitoring S Yan, X Yan Industrial & Engineering Chemistry Research 58 (23), 9952-9958, 2019 | 42 | 2019 |
| Data-driven individual–joint learning framework for nonlinear process monitoring Q Jiang, S Yan, X Yan, S Chen, J Sun Control Engineering Practice 95, 104235, 2020 | 22 | 2020 |
| Data-driven soft sensing for batch processes using neural network-based deep quality-relevant representation learning Q Jiang, Z Wang, S Yan, Z Cao IEEE Transactions on Artificial Intelligence, 2022 | 14 | 2022 |
| Quality-driven autoencoder for nonlinear quality-related and process-related fault detection based on least-squares regularization and enhanced statistics S Yan, X Yan Industrial & Engineering Chemistry Research 59 (26), 12136-12143, 2020 | 13 | 2020 |
| Joint monitoring of multiple quality-related indicators in nonlinear processes based on multi-task learning S Yan, X Yan Measurement 165, 108158, 2020 | 12 | 2020 |
| Monitoring of quality-relevant and quality-irrelevant blocks with characteristic-similar variables based on self-organizing map and kernel approaches S Yan, J Huang, X Yan Journal of Process Control 73, 103-112, 2019 | 12 | 2019 |
| Quality-relevant dynamic process monitoring based on dynamic total slow feature regression model S Yan, Q Jiang, H Zheng, X Yan Measurement Science and Technology 31 (7), 075102, 2020 | 10 | 2020 |
| Quality-relevant fault detection based on adversarial learning and distinguished contribution of latent variables to quality S Yan, X Yan Journal of Manufacturing Systems 61, 536-545, 2021 | 7 | 2021 |
| Robust chemical process monitoring based on CDC‐MVT‐PCA eliminating outliers and optimally selecting principal component J Huang, S Yan, X Yan The Canadian Journal of Chemical Engineering 97 (6), 1848-1857, 2019 | 7 | 2019 |
| Neural network aided approximation and parameter inference of stochastic models of gene expression Q Jiang, X Fu, S Yan, R Li, W Du, Z Cao, F Qian, R Grima BioRxiv, 2020.12. 15.422883, 2020 | 4 | 2020 |
| Cmmd: Cross-metric multi-dimensional root cause analysis S Yan, C Shan, W Yang, B Xu, D Li, L Qiu, J Tong, Q Zhang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 3 | 2022 |
| Neural representations for quality-related kernel learning and fault detection S Yan, L Lv, X Yan Soft Computing 27 (18), 13543-13551, 2023 | 2 | 2023 |
| Nonlinear quality-relevant process monitoring based on maximizing correlation neural network S Yan, X Yan Neural Computing and Applications 33 (16), 10129-10139, 2021 | 2 | 2021 |
| Learning Output Relevant Features by Joint Autoencoder S Yan, X Yan IEEE Transactions on Cybernetics, 2022 | 1 | 2022 |
| Fluid catalytic cracking process quality-driven fault detection based on partial least squares and deep feedforward neural network J Yang, J Li, S Yan, Y Wang, Y Zhang, X Yan Transactions of the Institute of Measurement and Control 46 (1), 78-92, 2024 | | 2024 |
Qingchao JiangProfessor, East China University of Science and TechnologyVerified email at ecust.edu.cn
