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Enhancing Monitoring Performance of Pharmaceutical Processes Using Dual-Attention Latent Dynamic Conditional State-Space Model.

, and . ASCC, page 227-232. IEEE, (2022)

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Probabilistic uncertainty based simultaneous process design and control with iterative expected improvement model., and . Comput. Chem. Eng., (2017)Prognostics of tool failing behavior based on autoassociative Gaussian process regression for semiconductor manufacturing., , and . ICIT, page 316-321. IEEE, (2020)Performance assessment for non-Gaussian systems by minimum entropy control and dynamic data reconciliation., , , , and . J. Frankl. Inst., 359 (8): 3930-3950 (2022)Accelerating reinforcement learning with case-based model-assisted experience augmentation for process control., , , and . Neural Networks, (January 2023)Facilitating Reinforcement Learning for Process Control Using Transfer Learning: Perspectives., , , , and . CoRR, (2024)A robust semi-supervised learning scheme for development of within-batch quality prediction soft-sensors., and . Eng. Appl. Artif. Intell., (2024)Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes., , and . IEEE Trans. Syst. Man Cybern. Syst., 54 (6): 3450-3460 (June 2024)Single Neuron Stochastic Predictive PID Control Algorithm for Nonlinear and Non-Gaussian Systems Using the Survival Information Potential Criterion., , , , and . Entropy, 18 (6): 218 (2016)Simultaneous data reconciliation and gross error detection for dynamic systems using particle filter and measurement test., and . Comput. Chem. Eng., (2014)Semi-Supervised Learning-Based Calibration Model Building of NIR Spectroscopy for In Situ Measurement of Biochemical Processes Under Insufficiently and Inaccurately Labeled Samples., , , and . IEEE Trans. Instrum. Meas., (2021)