Process Data Analytics via Probabilistic Latent Variable Models: A Tutorial Review von Ge, Zhiqiang

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Mixture Bayesian Regularization of PCR Model and Soft Sensing Application von Ge, Zhiqiang

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Deep Learning of Semisupervised Process Data With Hierarchical Extreme Learning Machine and Soft Sensor Application von Yao, Le, Ge, Zhiqiang

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Supervised Latent Factor Analysis for Process Data Regression Modeling and Soft Sensor Application von Ge, Zhiqiang

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Improving the Performance of Just-In-Time Learning-Based Soft Sensor Through Data Augmentation von Jiang, Xiaoyu, Ge, Zhiqiang

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Review of Recent Research on Data-Based Process Monitoring von Ge, Zhiqiang, Song, Zhihuan, Gao, Furong

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Distributed Parallel PCA for Modeling and Monitoring of Large-Scale Plant-Wide Processes With Big Data von Zhu, Jinlin, Ge, Zhiqiang, Song, Zhihuan

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Review on data-driven modeling and monitoring for plant-wide industrial processes von Ge, Zhiqiang

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A Probabilistic Just-in-Time Learning Framework for Soft Sensor Development With Missing Data von Yuan, Xiaofeng, Ge, Zhiqiang, Huang, Biao, Song, Zhihuan

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Online Updating Soft Sensor Modeling and Industrial Application Based on Selectively Integrated Moving Window Approach von Yao, Le, Ge, Zhiqiang

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Weighted Linear Dynamic System for Feature Representation and Soft Sensor Application in Nonlinear Dynamic Industrial Processes von Yuan, Xiaofeng, Wang, Yalin, Yang, Chunhua, Ge, Zhiqiang, Song, Zhihuan, Gui, Weihua

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Locally Weighted Kernel Principal Component Regression Model for Soft Sensing of Nonlinear Time-Variant Processes von Yuan, Xiaofeng, Ge, Zhiqiang, Song, Zhihuan

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Data Mining and Analytics in the Process Industry: The Role of Machine Learning von Ge, Zhiqiang, Song, Zhihuan, Ding, Steven X., Huang, Biao

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Mixture Bayesian regularization method of PPCA for multimode process monitoring von Ge, Zhiqiang, Song, Zhihuan

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A comparative study of just-in-time-learning based methods for online soft sensor modeling von Ge, Zhiqiang, Song, Zhihuan

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Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR von Yuan, Xiaofeng, Ge, Zhiqiang, Huang, Biao, Song, Zhihuan, Wang, Yalin

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Locally Weighted Prediction Methods for Latent Factor Analysis With Supervised and Semisupervised Process Data von Yao, Le, Ge, Zhiqiang

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Process Monitoring Based on Independent Component Analysis−Principal Component Analysis (ICA−PCA) and Similarity Factors von Ge, Zhiqiang, Song, Zhihuan

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Variational Bayesian Gaussian Mixture Regression for Soft Sensing Key Variables in Non-Gaussian Industrial Processes von Zhu, Jinlin, Ge, Zhiqiang, Song, Zhihuan

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Semisupervised Kernel Learning for FDA Model and its Application for Fault Classification in Industrial Processes von Ge, Zhiqiang, Zhong, Shiyong, Zhang, Yingwei

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