1. The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence

    Nechesov, A. V., Vityaev, E. E., Goncharov, S. S. & Sviridenko, D. I., 2025, In: Bulletin of Irkutsk State University, Series Mathematics. 54, p. 96-112 17 p., 7.

    Research output: Contribution to journalArticlepeer-review

  2. Tissue distribution of OL9-116, a Tdp1 inhibitor based on usnic acid, is significantly altered in Lewis lung carcinoma-bearing mice compared to healthy animals

    Okhina, A. A., Kornienko, T. E., Rogachev, A. D., Luzina, O. A., Popova, N. A., Nikolin, V. P., Zakharenko, A. L., Dyrkheeva, N. S., Pokrovsky, A. G., Salakhutdinov, N. F. & Lavrik, O. I., 15 Nov 2025, In: Journal of Pharmaceutical and Biomedical Analysis. 265, p. 117054 8 p., 117054.

    Research output: Contribution to journalArticlepeer-review

  3. Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge

    Pati, S., Linardos, A., Edwards, B., Sheller, M., Foley, P., Aristizabal, A., Zimmerer, D., Gruzdev, A., Martin, J., Shinohara, R. T., Reinke, A., Isensee, F., Parampottupadam, S., Parekh, K., Floca, R., Kassem, H., Baheti, B., Thakur, S., Kushibar, K., Lekadir, K., & 72 othersJiang, M., Yin, Y., Yang, H., Liu, Q., Chen, C., Dou, Q., Heng, P. A., Zhang, X., Zhang, S., Khan, M. I., Azeem, M. A., Jafaritadi, M., Alhoniemi, E., Kontio, E., Khan, S. A., Mächler, L., Ezhov, I., Kofler, F., Shit, S., Paetzold, J. C., Loehr, T., Wiestler, B., Peiris, H., Pawar, K., Zhong, S., Chen, Z., Hayat, M., Egan, G., Harandi, M., Isik Polat, E., Polat, G., Kocyigit, A., Temizel, A., Tuladhar, A., Tyagi, L., Souza, R., Forkert, N. D., Mouches, P., Wilms, M., Shambhat, V., Maurya, A., Danannavar, S. S., Kalla, R., Anand, V. K., Krishnamurthi, G., Nalawade, S., Ganesh, C., Wagner, B., Reddy, D., Das, Y., Yu, F. F., Fei, B., Madhuranthakam, A. J., Maldjian, J., Singh, G., Ren, J., Zhang, W., An, N., Hu, Q., Zhang, Y., Zhou, Y., Siomos, V., Tarroni, G., Passerrat-Palmbach, J., Rawat, A., Zizzo, G., Kadhe, S. R., Epperlein, J. P., Braghin, S., Tuchinov, B., Maier-Hein, K. (ed.) & Bakas, S. (ed.), 8 Jul 2025, In: Nature Communications. 16, 1, p. 6274 20 p., 6274.

    Research output: Contribution to journalArticlepeer-review

  4. Towards Verification Reflex Programs in the Rodin Platform

    Shabanova, M. & Garanina, N., 8 Aug 2025, International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM. IEEE Computer Society, p. 1490-1495 6 p. (International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices, EDM).

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

  5. Transfer Learning Approaches for Brain Metastases Screenings

    Luu, M. S. K., Tuchinov, B. N., Suvorov, V., Kenzhin, R. M., Amelina, E. V. & Letyagin, A. Y., Nov 2024, In: Biomedicines. 12, 11, 2561.

    Research output: Contribution to journalArticlepeer-review

  6. Transfer Learning for Transformer-Based Modeling of Nonlinear Pulse Evolution in Er-Doped Fiber Amplifiers

    Bednyakova, A. E., Gemuzov, A. S., Mishevsky, M. S., Saraeva, K. P., Redyuk, A. A., Mkrtchyan, A. A., Nasibulin, A. G. & Gladush, Y. G., 12 Dec 2025, In: Laser and Photonics Reviews. 14 p., e02014.

    Research output: Contribution to journalArticlepeer-review

  7. Tunable Optical Parametric Oscillator Based on MgO:PPLN and HgGa2S4 Crystals Pumped by an Nd:YAG Laser with Increased Energy Characteristics

    Erushin, E. Y., Yakovin, M. D., Latkin, N. I., Podzyvalov, S. N., Kostyukova, N. Y. & Boyko, A. A., Apr 2024, In: Bulletin of the Lebedev Physics Institute. 51, Suppl 1, p. S39-S50 12 p.

    Research output: Contribution to journalArticlepeer-review

  8. Two-component swirling jet atomization with static vortex generators

    Vozhakov, I., Hrebtov, M., Yavorsky, N. & Mullyadzhanov, R., Jul 2025, In: Physics of Fluids. 37, 7, 13 p., 073305.

    Research output: Contribution to journalArticlepeer-review

  9. Unsupervised Learning for Detection of Cognitive Distortions in Patient Narratives

    Bobo, S. & Kolonin, A., 2026, Advances in Neural Computation, Machine Learning, and Cognitive Research IX. Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V., Tiumentsev, Y. & Klimov, V. V. (eds.). Springer, p. 545-562 18 p. 43. (Studies in Computational Intelligence; vol. 1241 SCI).

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

  10. Validation of Smagorinsky LES turbulence model in FluidX3D LBM: in-place vs central difference

    Plekhanov, M. & Mullyadzhanov, R., 14 Oct 2024, In: E3S Web of Conferences. 578, 6 p., 01029.

    Research output: Contribution to journalConference articlepeer-review

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