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  1. Data-driven turbulence modeling for fluid flow and heat transfer in peripheral subchannels of a rod bundle

    Li, H., Yakovenko, S., Ivashchenko, V., Lukyanov, A., Mullyadzhanov, R. & Tokarev, M., 2024, In: Physics of Fluids. 36, 2

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

  2. Data-driven regularization of inverse problem for SEIR-HCD model of COVID-19 propagation in Novosibirsk region

    Krivorotko, O. & Zyatkov, N. Y., 2022, In: Eurasian Journal of Mathematical and Computer Applications. 10, 1, p. 51-68 18 p.

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

  3. 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

  4. Cross-Domain Robustness of Transformer-Based Keyphrase Generation

    Glazkova, A. & Morozov, D., 2024, Communications in Computer and Information Science. Springer, p. 249-265 17 p. 19. (Communications in Computer and Information Science; vol. 2086 CCIS).

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

  5. CPU-time and RAM memory optimization for solving dynamic inverse problems using gradient-based approach

    Klyuchinskiy, D. V., Novikov, N. S. & Shishlenin, M. A., 15 Aug 2021, In: Journal of Computational Physics. 439, 110374.

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

  6. Corrigendum to “On using unstabilized compressed earth blocks as suspended weights in gravity energy storages” [J. Energy Storage 72 (2023) 108764] (Journal of Energy Storage (2023) 72(PE), (S2352152X23021618), (10.1016/j.est.2023.108764))

    Kropotin, P., Penkov, O. & Marchuk, I., 20 Dec 2023, In: Journal of Energy Storage. 73, 109138.

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

  7. Convolutional Neural Networks with Multiple Layers per Span for Nonlinearity Mitigation in Long-Haul WDM Transmission Systems

    Sidelnikov, O., Redyuk, A., Sygletos, S., Fedoruk, M. & Turitsyn, S., Jun 2021, 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021. Institute of Electrical and Electronics Engineers Inc., 1 p. Paper CI-P.6. (2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2021).

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

  8. Convolutional neural networks with multiple layers per span for nonlinearity mitigation in long-haul WDM transmission systems

    Sidelnikov, O., Redyuk, A., Sygletos, S., Fedoruk, M. & Turitsyn, S., 2021, The European Conference on Lasers and Electro-Optics, CLEO/Europe 2021. The Optical Society, ci_p_6. (Optics InfoBase Conference Papers).

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

  9. Convex Optimization with Inexact Gradients in Hilbert Space and Applications to Elliptic Inverse Problems

    Matyukhin, V., Kabanikhin, S., Shishlenin, M., Novikov, N., Vasin, A. & Gasnikov, A., 2021, Mathematical Optimization Theory and Operations Research - 20th International Conference, MOTOR 2021, Proceedings. Pardalos, P., Khachay, M. & Kazakov, A. (eds.). Springer, p. 159-175 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12755 LNCS).

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

  10. Control Theory Problems and the Rashevskii–Chow Theorem on a Cartan Group

    Greshnov, A. V. & Zhukov, R. I., Sept 2024, In: Siberian Mathematical Journal. 65, 5, p. 1096-1111 16 p.

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

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