17 citations to https://www.mathnet.ru/rus/zvmmf10376
  1. 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  crossref
  2. 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  crossref  mathscinet  zmath  adsnasa  isi
  3. 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  crossref  isi  scopus
  4. Y. Kapushev, I. Oseledets, E. Burnaev, “Tensor completion via Gaussian process-based initialization”, SIAM J. Sci. Comput., 42:6 (2020), A3812–A3824  crossref  mathscinet  zmath  isi
  5. E. V. Burnaev, “Algorithmic foundations of predictive analytics in industrial engineering design”, J. Commun. Technol. Electron., 64:12 (2019), 1485–1492  crossref  isi
  6. 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  crossref
  7. 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  crossref  isi  scopus
  8. Das S., Roy S., Sambasivan R., “Fast Gaussian Process Regression For Big Data”, Big Data Res., 14 (2018), 12–26  crossref  isi
  9. 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  crossref  isi
  10. 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  crossref  isi
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