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  1. Advancing graph neural network architecture for fluid flow and heat transfer surrogate modeling: Variable boundary conditions and geometry

    Travnikov, V., Plokhikh, I. & Mullyadzhanov, R., 1 Dec 2024, In: Physics of Fluids. 36, 12, 127117.

    Research output: Contribution to journal › Article › peer-review

  2. Data-Driven Prediction of Unsteady Vortex Phenomena in a Conical Diffuser

    Skripkin, S., Suslov, D., Plokhikh, I., Tsoy, M., Gorelikov, E. & Litvinov, I., 2023, In: Energies. 16, 5, 2108.

    Research output: Contribution to journal › Article › peer-review

  3. Energy spectra of elemental groups of cosmic rays with the KASCADE experiment data and machine learning

    Kuznetsov, M. Y., Petrov, N., Plokhikh, I. & Sotnikov, V., 1 May 2024, In: Journal of Cosmology and Astroparticle Physics. 2024, 5, 125.

    Research output: Contribution to journal › Article › peer-review

  4. Measurable Metrics of Mesenchymal Stem Cell Aging

    Kalashnikova, D. A., Romanov, S. E., Maksimov, D. A., Plokhikh, I. A., Epifanov, R. Y., Mullyadjanov, R. I., Sidelnikov, L. O., Antoshina, P. A., Osipov, Y. A., Shloma, V. V., Budilina, A. A., Samoylova, E. M., Baklaushev, V. P. & Laktionov, P. P., 2025, In: Sovremennye Tehnologii v Medicine. 17, 5, p. 5-30 26 p., 1.

    Research output: Contribution to journal › Article › peer-review

  5. Methods of machine learning for the analysis of cosmic rays mass composition with the KASCADE experiment data

    Kuznetsov, M. Y., Petrov, N. A., Plokhikh, I. A. & Sotnikov, V. V., 1 Jan 2024, In: Journal of Instrumentation. 19, 1, P01025.

    Research output: Contribution to journal › Article › peer-review

  6. New insights from old cosmic rays: A novel analysis of archival KASCADE data

    Kostunin, D., Plokhikh, I., Ahlers, M., Tokareva, V., Lenok, V., Bezyazeekov, P., Golovachev, S., Sotnikov, V., Mullyadzhanov, R. & Sotnikova, E., 18 Mar 2022, In: Proceedings of Science. 395, 319.

    Research output: Contribution to journal › Conference article › peer-review

  7. Parametric RANS Simulation of a Cavitation Flow in the Channel of a Control Valve Cage

    Ivashchenko, E. I., Ivashchenko, V. A., Plokhikh, I. A., Mardanov, A. R., Melemchuk, I. A., Pimenov, N. K. & Mullyadzhanov, R. I., Mar 2023, In: Journal of Applied and Industrial Mathematics. 17, 1, p. 86-93 8 p.

    Research output: Contribution to journal › Article › peer-review

  8. Pattern recognition for bubbly flows with vapor or gas-liquid interfaces using U-Net architecture

    Seredkin, A., Plokhikh, I., Mullyadzhanov, R., Malakhov, I., Serdyukov, V., Surtaev, A., Chinak, A., Lobanov, P. & Tokarev, M., 14 Nov 2020, Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020. Institute of Electrical and Electronics Engineers Inc., p. 5-8 4 p. 9303175. (Proceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  9. PREDICTION OF FLOW PATTERNS OF LIQUID-LIQUID FLOWS IN TSHAPED MICROCHANNELS USING MACHINE LEARNING APPROACHES

    Yagodnitsyna, A. A., Plohih, I. A., Kovalev, A. V. & Bilsky, A. V., 2022, p. 369.

    Research output: Contribution to conference › Paper › peer-review

  10. Reconstruction of sub-threshold events of cosmic-ray radio detectors using an autoencoder

    the Tunka-Rex Collaboration, 18 Mar 2022, In: Proceedings of Science. 395, 223.

    Research output: Contribution to journal › Conference article › peer-review

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