Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes
Gao, Jingyi & Chung, S. (2024). Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes. arXiv preprint arXiv:2407.16935.
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Gao, Jingyi & Chung, S. (2024). Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes. arXiv preprint arXiv:2407.16935.
Chung, S., & Kontar, R. A. (2024). Real-time Adaptation for Condition Monitoring Signal Prediction using Label-aware Neural Processes. arXiv preprint arXiv:2403.16377.
Chung, S. & Kontar, R. (2023) Federated Multi-output Gaussian Processes. Technometrics. Advance online publication. DOI: 10.1080/00401706.2023.2238834.
Chung, S. & Al Kontar, R. Federated Condition Monitoring Signal Prediction With Improved Generalization. IEEE Transactions on Reliability. Advance online publication. doi: 10.1109/TR.2023.3283348.
Chung, S., Al Kontar, R., & Wu, Z. (2022). Weakly Supervised Multi-output Regression via Correlated Gaussian Processes. INFORMS Journal on Data Science 1(2):115-137.
Chung, S., Chou, C. H., Fang, X., Al Kontar, R., & Okwudire, C. (2022). A Multi-Stage Approach for Knowledge-Guided Predictions With Application to Additive Manufacturing. IEEE Transactions on Automation Science and Engineering, 19(3), 1675-1687.
Chung, S. & Kontar, R. (2021). Functional principal component analysis for extrapolating multistream longitudinal data. IEEE Transactions on Reliability, 70(4), 1321-1331.
Wang, J., Chung, S., AlShelahi, A., Kontar, R., Byon, E., & Saigal, R. (2021). Look-ahead decision making for renewable energy: A dynamic “predict and store” approach. Applied Energy, 296, 117068.
Chung, S., Park, Y. W., & Cheong, T. (2020). A mathematical programming approach for integrated multiple linear regression subset selection and validation. Pattern Recognition, 108, 107565.