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О качестве обучения искусственных нейронных сетей без предобработки исходных данных в условиях их ограниченного набора
Прикладная математика и вопросы управления. 2023. № 3. С. 67–83.
Кожемякин Л. В., Alekseev A.
Keywords: нейронные сети
Фирсанова В. И., Journal of Mathematical Sciences 2024 Vol. 285 No. 1 P. 112–125
Text-to-image models use user-generated prompts to produce images. Such text-to-image models as DALL-E 2, Imagen, Stable Diffusion, and Midjourney can generate photorealistic or similar to human-drawn images. Apart from imitating human art, large text-to-image models have learned to produce combinations of pixels reminiscent of captions in natural languages. For example, a generated image might contain ...
Added: September 9, 2026
Фирсанова В. И., Человек: образ и сущность. Гуманитарные аспекты 2025 Vol. 2 No. 62 P. 203–214
Abstract. The paper highlights prompt engineering in academic setting to reduce plagiarism and increase students' interest. The research problem is the lack of a unified methodology for using artificial intelligence in education. The paper aims to create a generative artificial intelligence user interface, the Virtual Teaching Assistant. Teachers were interviewed, the first collection of presets ...
Added: September 9, 2026
Вохминцев И. В., Вестник международных организаций: образование, наука, новая экономика 2026 Т. 21 № 2
The EAEU and the CSTO are Russia’s principal regional international organisations. Understanding, assessing, and analysing the foreign-policy positions of the countries that belong to them is a matter of the state’s national interests. This determines the purpose of the study: to identify the level and the form of cohesion in the voting of EAEU and ...
Added: September 7, 2026
Proskurnina E., Liaukovich K., Bychkovskaya L. et al., Metabolites 2023 Vol. 13 No. 1 P. 73
Added: September 7, 2026
Alshanskaia E., Portnova G., Liaukovich K. et al., Frontiers in Neuroscience 2024 Vol. 18
Added: September 7, 2026
Зуенко Д. О., Trofimova E., Хайдарова И., IEEE Access 2026 Vol. 14 P. 121339–121357
Oil spill segmentation in Synthetic Aperture Radar (SAR) images is limited by noisy annotations in publicly available datasets and by architectural choices that interact with label quality in opposing directions. First, we introduce a manually refined version of the Deep-SAR Oil Spill (SOS) dataset, in which 36.25% of masks are corrected for false positives, missed ...
Added: September 7, 2026
Kelbert M., Statistics 2026 Vol. 60
We present variational representations for the weighted divergencies
and exponential error function, and discuss implications for the
statistical inference and entropic optimal transport. ...
Added: September 7, 2026
Liaukovich K., Panfilova E., Khayrullina G. et al., International Journal of Psychophysiology 2025 Vol. 207 P. 112475
Added: September 5, 2026
Liaukovich K., Bainbridge E., Khayrullina G. et al., Neuroscience and Behavioral Physiology 2026 Vol. 56 P. 10–19
Added: September 5, 2026
Kashevarova O., Portnova G., Khayrullina G. et al., Frontiers in Psychiatry 2026 Vol. 17 P. 1776019
Added: September 5, 2026
Неверов В. Д., Красавин А. В., Vagov A. et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 P. 1–6
We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...
Added: September 5, 2026
Sheshukova M., Durmus A., Khusainov M. et al., Statistics 2026 P. 1–25
In this paper, we consider the problem of Gaussian approximation for the online linear regression task. We derive the corresponding rates for the setting of a constant stepsize and study the explicit dependence of the convergence rate on the problem dimension d and quantities related to the design matrix. When the number of iterations n is known in advance, ...
Added: September 4, 2026
Proceedings of Machine Learning Research , 2026.
Added: September 4, 2026
Khodadoust J., Kulikova S., Khodadoust F., Biomedical Signal Processing and Control 2027 Vol. 129 P. 111284–111284
Acute ischemic stroke (AIS) analysis from two-dimensional (2D) clinical imaging is hindered by uncontrolled slice tilt and geometric inconsistencies that violate the assumptions of pose-agnostic deep learning (DL) models. This paper proposes a unified geometry-aware, frequency-domain framework for tilted slice localization and ischemic stroke segmentation that explicitly decouples pose estimation from lesion analysis. The method ...
Added: September 2, 2026
IEEE, 2026.
On behalf of the Organizing Committee, it is my great pleasure to extend a warm
welcome to all participants of the Fourth International IEEE Conference on
Distributed Computing and High-Performance Computing (DCHPC 2026), held
in Tehran from May 10–11, 2026. This conference is jointly organized by the
School of Computer Science at the Institute for Research in Fundamental
Sciences (IPM) ...
Added: September 2, 2026
S.M. Avdoshin, Patrushev K. A., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4-2 P. 245–256
The cardinality-constrained Markowitz problem is NP-hard and traditionally solved with commercial MIQP solvers. Following the 2022 export restrictions that rendered both commercial MIQP software and cloud quantum platforms (IBM Quantum, D-Wave Leap) inaccessible from the Russian Federation, practitioners require open-source alternatives. This paper systematically compares three solver families for the discrete mean-variance problem: two open-source ...
Added: August 27, 2026
Seul: PMLR, 2026.
Added: June 4, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Ролинский С. О., Dvoynikova A., В кн.: Альманах научных работ молодых ученых Университета ИТМОТ. 2.: Университет ИТМО, 2022. С. 336–340.
В работе рассмотрены основные существующие подходы к автоматическому распознаванию речи, а также проводится сравнительный анализ открытых компьютерных систем распознавания речи. Для экспериментальных исследований эффективности работы рассматриваемых систем используется речевой корпус LibriSpeech. ...
Added: April 24, 2026
Dvoynikova A., Садикова А. А., В кн.: Сборник трудов X Конгресса молодых ученыхТ. 1.: Университет ИТМО, 2021.
В работе рассматривается применение различных планировщиков обучения (англ. scheduler) нейронных сетей для задачи текстонезависимой верификации дикторов. Для экспериментальных исследований использовалась база данных VoxCeleb1, которая содержит в себе различные речевые высказывания 1211 дикторов. В работе проводился анализ влияния различных планировщиков обучения нейронных сетей, представленных в библиотеке PyTorch языка программирования Python, а также 2 алгоритма планировщика, представленных ...
Added: April 24, 2026
Efremov A., Portnoy S., Волошин А. Д., Первая миля 2025 № 8 С. 20–28
Выполнен комплексный обзор методов машинного обучения (ML), применяемых для повышения устойчивости сигнала к помехам в каналах связи. Бурное развитие поколений беспроводной связи, активная разработка концепции 6G предъявляют высокие требования к задержке, скорости и надежности передачи данных. Традиционные подходы к защите от помех, основанные на строгих аналитических моделях, зачастую не справляются с хаотичной природой плотных гетерогенных ...
Added: April 4, 2026
Пермь: Пермский государственный национальный исследовательский университет, 2024.
This collection presents the proceedings of the Ninth All-Russian Scientific and Practical Conference with International Participation, "Artificial Intelligence in Solving Current Social and Economic Problems of the 21st Century," which was held October 17–18, 2024, in Perm. The collection is intended for researchers and educators, lecturers, postgraduate and master's students, undergraduates, and anyone interested in ...
Added: November 19, 2025
Penskaja E., Имагология и компаративистика 2025 № 23 С. 380–389
The book Artificial Intelligence, Archives and Manuscripts. New Relationships between the Virtual Archive and Its Referent (2025) is presented. This collective monograph discusses both technological and legal, intellectual issues that researchers and archivists face in automated work with manuscript heritage, artificial intelligence and neural networks. ...
Added: October 30, 2025
Surkov A., Sergei Koltcov, Ignatenko V. et al., Physica A: Statistical Mechanics and its Applications 2025 Vol. 681 Article 131085
Neural networks are powerful tools capable of achieving state-of-the-art performance across a wide range of tasks; however, their effectiveness often comes at the cost of extremely large numbers of parameters, which can hinder their deployment in resource-constrained environments. To address this issue, various pruning techniques have been proposed to reduce model size and complexity while ...
Added: October 30, 2025