1. 2023
  2. The topology of fMRI-based networks defines the performance of a graph neural network for the classification of patients with major depressive disorder

    Pitsik, E. N., Maximenko, V. A., Kurkin, S. A., Sergeev, A. P., Stoyanov, D., Paunova, R., Kandilarova, S., Simeonova, D. & Hramov, A. E., 1 Feb 2023, In: Chaos, Solitons and Fractals. 167, 113041.

    Research output: Contribution to journalArticlepeer-review

  3. Classification of graph topologies by machine learning methods: book chapter

    Bobakov, V., Koryukin, E., Butorova, A. & Sergeev, A., 2023, Proceedings - 7th Scientific School: Dynamics of Complex Networks and their Applications, DCNA 2023: book. Institute of Electrical and Electronics Engineers Inc., p. 32-35 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

  4. Influence of the transfer function of the NARX network hidden layer on the accuracy of predicting the changes in the surface methane concentration

    Medvedev, A., Sergeev, A., Buevich, A., Shichkin, A. & Sergeeva, M., 2023, In: AIP Conference Proceedings. 2849, 1, 090025.

    Research output: Contribution to journalConference articlepeer-review

  5. Статистические методы в системах управления качеством (в полиграфии): учебное пособие

    Арапов, С. Ю., Сергеев, А. П., Арапова, С. П., Мильдер, О. Б. (ed.) & Мартюшев, Л. М., 2023, Екатеринбург: Издательство Уральского университета. 184 p.

    Research output: Book/ReportScholarly editionpeer-review

  6. 2022
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