1. Application of Analysis Methods for Ring Resonator Characteristics to Simulating Soliton Fiber-Optic Communication Lines

    Patrin, G. A., Chekhovskoy, I. S., Sidelnikov, O. S., Shtyrina, O. V. & Fedoruk, M. P., 15 Feb 2025, In: Bulletin of the Lebedev Physics Institute. 51, Suppl 10, p. S834-S847 14 p.

    Research output: Contribution to journalArticlepeer-review

  2. An optical parametric oscillator based on BaGa2GeS6 with energy exceeding 2 mJ at 6.45 μm

    Erushin, E. Y., Sere, S. E., Vostrikova, M. V., Boyko, A. A., Shevyrdyaeva, G. S., Badikov, D. V., Karapuzikov, A. A. & Kostyukova, N. Y., Mar 2026, In: Infrared Physics and Technology. 154, 6 p., 106393.

    Research output: Contribution to journalArticlepeer-review

  3. An Explanation Method for Semantic Segmentation Enhance Brain Tumor Classification

    Kenzhin, R., Luu, M. S. K., Pavlovskiy, E. & Tuchinov, B., 2025, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer, p. 319-330 12 p. 23. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; vol. 15406 LNCS).

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

  4. Analysis of Narrowband Lasing Parameters in a Random Fiber Raman Laser for Ultra-High-Resolution Spectroscopy with a Scanning Spectrometer

    Gorbunov, O. A. & Vatnik, I. D., Dec 2025, In: JETP Letters. 122, 11, p. 777-781 5 p.

    Research output: Contribution to journalArticlepeer-review

  5. An Accurate and Efficient Approach to Knowledge Extraction from Scientific Publications Using Structured Ontology Models, Graph Neural Networks, and Large Language Models

    Ivanisenko, T. V., Demenkov, P. S. & Ivanisenko, V. A., 3 Nov 2024, In: International Journal of Molecular Sciences. 25, 21, 11811.

    Research output: Contribution to journalArticlepeer-review

  6. A Learning Path to Functional Programming (and What Students can see on the Path)

    Gorodnyaya, L., Kondratyev, D. & Shilov, N., 2025, Agents and Multi-agent Systems: Technologies and Applications 2024. Howlett, R. J. & Jain, L. C. (eds.). Springer, Vol. 406. p. 293-302 10 p. 25. (Smart Innovation, Systems and Technologies; vol. 406).

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

  7. AIMarkerFinder: AI-Assisted Marker Discovery Based on an Integrated Approach of Autoencoders and Kolmogorov–Arnold Networks

    Demenkov, P. S., Ivanisenko, T. V. & Ivanisenko, V. A., 2026, In: Informatics. 13, 1, 13 p., 2.

    Research output: Contribution to journalArticlepeer-review

  8. AI-Assisted Identification of Primary and Secondary Metabolomic Markers for Postoperative Delirium

    Ivanisenko, V. A., Rogachev, A. D., Makarova, A-L. A., Basov, N. V., Gaisler, E. V., Kuzmicheva, I. N., Demenkov, P. S., Venzel, A. S., Ivanisenko, T. V., Antropova, E. A., Kolchanov, N. A., Plesko, V. V., Moroz, G. B., Lomivorotov, V. V. & Pokrovsky, A. G., Nov 2024, In: International Journal of Molecular Sciences. 25, 21, 11847.

    Research output: Contribution to journalArticlepeer-review

  9. A Hybrid Method for Solving the Two-Dimensional Poisson Equation: Combining U-Net and Conjugate Gradient Method

    Sakharov, D. I., Tsgoev, C. A. & Mullyadzhanov, R. I., 2025, In: Lobachevskii Journal of Mathematics. 46, 8, p. 3777-3790 14 p., 16.

    Research output: Contribution to journalArticlepeer-review

  10. 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 journalArticlepeer-review

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