17 citations to https://www.mathnet.ru/rus/zvmmf10376
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I. A. Konovalov, A. N. Sokolov, A. A. Barinov, T. K. Zyryanova, “Developing a Technique for Constructing Surrogate Models of Equipment on the Example of a Hydraulic Model of a Gas-Removal Device”, Therm. Eng., 70:2 (2023), 139
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W. Wang, Q. Yu, M. Fasli, “Altering Gaussian process to Student-$t$ process for maximum distribution construction”, Int. J. Syst. Sci., 52:4 (2021), 727–755
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V. C. Angadi, A. Mousavi, D. Bartolome, M. Tellarini, M. Fazziani, “Causal modelling for predicting machine tools degradation in high speed production process(star)”, IFAC-PapersOnLine, 53:3 (2020), 271–275
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Y. Kapushev, I. Oseledets, E. Burnaev, “Tensor completion via Gaussian process-based initialization”, SIAM J. Sci. Comput., 42:6 (2020), A3812–A3824
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E. V. Burnaev, “Algorithmic foundations of predictive analytics in industrial engineering design”, J. Commun. Technol. Electron., 64:12 (2019), 1485–1492
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Zhongda Tian, Yi Ren, Gang Wang, “A variable sampling period scheduling method for networked control system under resource constraints”, Australian Journal of Electrical and Electronics Engineering, 16:4 (2019), 289
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A. Kuleshov, A. Bernstein, E. Burnaev, “Kernel regression on manifold valued data”, 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), IEEE, 2018, 120–129
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Das S., Roy S., Sambasivan R., “Fast Gaussian Process Regression For Big Data”, Big Data Res., 14 (2018), 12–26
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A. Kuleshov, A. Bernstein, E. Burnaev, Yu. Yanovich, “Machine learning in appearance-based robot self-localization”, 2017 16Th IEEE International Conference on Machine Learning and Applications, ICMLA 2017, eds. X. Chen, B. Luo, F. Luo, V. Palade, M. Wani, IEEE, 2017, 106–112
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R. Rivera, E. Burnaev, “Forecasting of commercial sales with large scale Gaussian processes”, 2017 17Th IEEE International Conference on Data Mining Workshops, ICDMW 2017, International Conference on Data Mining Workshops, eds. R. Gottumukkala, X. Ning, G. Dong, V. Raghavan, S. Aluru, G. Karypis, L. Miele, X. Wu, IEEE, 2017, 625–634