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  1. Default Mode Network Connections Supporting Intra- Individual Variability in Typically Developing Primary School Children: An EEG Study

    Privodnova, E. Y., Slobodskaya, H. R., Bocharov, A. V., Saprigyn, A. E. & Knyazev, G. G., Oct 2020, In: Neuropsychology. 34, 7, p. 811-823 13 p.

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

  2. DEER/PELDOR Study of the Effect of Extremely Low Concentrations of the Antimicrobial Peptide Chalciporin A on the Membrane Lipid Organization

    Kashnik, A. S., Syryamina, V. N., Biondi, B., Peggion, C., Formaggio, F. & Dzuba, S. A., Mar 2023, In: Applied Magnetic Resonance. 54, 3, p. 401-414 14 p.

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

  3. Deep sub-Doppler cooling of Mg in MOT formed by light waves with elliptical polarization

    Prudnikov, O. N., Brazhnikov, D. V., Taichenachev, A. V., Yudin, V. I. & Goncharov, A. N., 16 Feb 2017, In: Journal of Physics: Conference Series. 793, 1, 9 p., 012021.

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

  4. Deep reinforcement learning for self-tuning laser source of dissipative solitons

    Kuprikov, E., Kokhanovskiy, A., Serebrennikov, K. & Turitsyn, S., Dec 2022, In: Scientific Reports. 12, 1, 7185.

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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

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