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  1. Deep Reinforcement Learning Control of Cylinder Flow Using Rotary Oscillations at Low Reynolds Number

    Tokarev, M., Palkin, E. & Mullyadzhanov, R., 2 Nov 2020, In: Energies. 13, 22, 11 p., 5920.

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

  2. Deep reinforcement learning algorithm for self-tuning 8-figure fiber laser

    Kokhanovskiy, A., Kuprikov, E., Serebrennikov, K. & Turitsyn, S., 2021, The European Conference on Lasers and Electro-Optics, CLEO/Europe 2021. The Optical Society, cj_4_3. (Optics InfoBase Conference Papers).

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

  3. Deep reinforcement learning algorithm for self-tuning 8-figure fiber laser

    Kokhanovskiy, A., Kuprikov, E., Serebrennikov, K. & 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. (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

  4. Deep-red phosphorescent organic–inorganic hybrid Mn(II) complexes based on 2-(diphenylphosphoryl)-N,N-diethylacetamide ligand

    Artem'ev, A. V., Berezin, A. S., Brel, V. K., Morgalyuk, V. P. & Samsonenko, D. G., 1 Jul 2018, In: Polyhedron. 148, p. 184-188 5 p.

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

  5. Deep Neural Networks with Time-Domain Synthetic Photonic Lattices

    Pankov, A. V., Sidelnikov, O. S., Vatnik, I. D., Churkin, D. V. & Sukhorukov, A. A., 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., (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

  6. Deep neural networks with time-domain synthetic photonic lattices

    Pankov, A. V., Sidelnikov, O. S., Vatnik, I. D., Churkin, D. V. & Sukhorukov, A. A., 2021, European Quantum Electronics Conference, EQEC 2021. The Optical Society, jsiv_p_3. (Optics InfoBase Conference Papers).

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

  7. Deep Multimodal Fusion Network for the Retinogeniculate Visual Pathway Segmentation

    Xie, L., Yang, L., Zeng, Q., He, J., Huang, J., Feng, Y., Amelina, E. & Amelin, M., 2023, Chinese Control Conference, CCC. Institute of Electrical and Electronics Engineers Inc., p. 7946-7950 5 p.

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

  8. Deep Methane Oxidation over Pd–Glass Fiber Catalysts Prepared by Chemical Vapor Deposition

    Suknev, A. P., Dorovskikh, S. I., Borisova, D. A., Sadovskaya, E. M., Zhezhera, M., Maximovskii, E. A., Svintsitskii, D. A., Derevshchikov, V. S. & Vikulova, E. S., 17 Aug 2026, In: Catalysis in Industry. 18, 3, p. 292-302 11 p.

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

  9. Deep macroscopic pure-optical potential for laser cooling and trapping of neutral atoms

    Prudnikov, O. N., Ilenkov, R. Y., Taichenachev, A. V., Yudin, V. I. & Bagaev, S. N., Oct 2023, In: Physical Review A. 108, 4, 043107.

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

  10. Deep machine learning for STEM image analysis

    Nartova, A. V., Matveev, A. V., Kovtunova, L. M. & Okunev, A. G., Nov 2024, In: Mendeleev Communications. 34, 6, p. 774-775 2 p.

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

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