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Soft Margin Spectral Normalization for GANs
Computing and Software for Big Science. 2024. Vol. 8. No. 1. Article 12.
In this paper, we explore the use of Generative Adversarial Networks (GANs) to speed up the simulation process while ensuring that the generated results are consistent in terms of physics metrics. Our main focus is the application of spectral normalization for GANs to generate electromagnetic calorimeter (ECAL) response data, which is a crucial component of the LHCb. We propose an approach that allows to balance between model’s capacity and stability during training procedure, compare it with previously published ones and study the relationship between proposed method’s hyperparameters and quality of generated objects. We show that the tuning of normalization method’s hyperparameters boosts the quality of generative model.
Andreeva S., Gavrilov A. A., Dzhikirba K. R. et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 114 Article 134515
We examine plasma excitations with linear dispersion in a system of superconducting electrons in thin
NbN disks. Using frequency-domain terahertz spectroscopy, we study the evolution of plasmons up to critical
temperature Tc. The observed excitations tend to shift to the lower frequencies while temperature is increasing
and the spectral features vanish at T > Tc. We study the ...
Added: September 23, 2026
Образцова А. А., Ivanov K., Moiseev E. et al., Journal of Physics D: Applied Physics 2026 Vol. 59 No. 30 P. 305103
We demonstrate a thermo-optically tunable microlaser based on an InGaAs/GaAs quantum-dot (QD) active region employing a deformed limaçon-shaped cavity. The asymmetric geometry effectively lifts the degeneracy of high-Q whispering-gallery modes, enabling single-mode lasing. A side-mode suppression ratio exceeds 25 dB over a wide current range. Under continuous-wave electrical pumping, the device achieves a peak output power ...
Added: September 23, 2026
Budkov Y., Journal of Chemical Physics 2026 Vol. 165 No. 12 Article 124105
Exact theories of electrolyte structure must satisfy the nonlocal constraints imposed by electrostatic screening, yet these constraints are most commonly formulated only for homogeneous bulk systems and at the level of two-point correlations. Here, we develop a unified field-theoretic framework that extends them to general inhomogeneous ionic fluids and nonlinear charge correlations. Using a standard ...
Added: September 22, 2026
Боровицкая И. В., Пименов В. Н., Коршунов С. Н. et al., Перспективные материалы 2026 № 10 С. 37–54
Проведено сравнение, обобщение и систематизация механизмов эрозии и разрушения
поверхности малоактивируемых материалов, перспективных для использования в
качестве материалов вакуумной камеры термоядерных реакторов: ванадия, его сплава
V – 10 Ti – 6 Cr – 0,05 Zr – 0,1 Si и вольфрама при последовательном воздействии на
них ионных и тепловых потоков. Тепловые потоки имитировали с помощью мощного
импульсного лазерного излучения (ЛИ), создаваемого ...
Added: September 22, 2026
Iontsev M.A., Mukhin S. I., Fistul M. V., Physical Review B: Condensed Matter and Materials Physics 2016 Vol. 94 No. 17 P. 174–510
We report a theoretical study of the ac response of superconducting quantum metamaterials (SQMs), i.e., an array of qubits (two-level systems) embedded in a low-dissipative resonator. By making use of a particular example of a SQM, namely the array of charge qubits capacitively coupled to the resonator, we obtain a second-order phase transition between an ...
Added: September 22, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Risk Analysis 2026 Vol. 46 No. 4 P. 1–26
Heated tobacco products (HTPs) are marketed as alternatives to conventional cigarettes with a potential reduced risk profile. Yet, their actual impact on cancer and noncancer disease risk remains uncertain and requires rigorous quantitative assessment. In this study, we develop a unified and transparent computational framework for toxicological risk assessment of HTPs, integrating chemical emissions data ...
Added: September 22, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 855–862
Tasks related to the automation of medical data processing are becoming more urgent. Particular attention is paid to systems for monitoring and analyzing human physiological parameters. Such systems often use specialized sensors to capture biomedical images, such as infrared cameras. This article describes our study of the problem of segmenting the eye pupil and iris ...
Added: September 21, 2026
Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854
Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Optical Memory and Neural Networks (Information Optics) 2024 Vol. 33 P. 424–434
This study explores the development of classifiers for microbial images, specifically focusing on streptococci captured via microscopy of live samples. Our approach uses AutoML-based techniques and automates the creation and analysis of feature spaces to produce optimal descriptors for classifying these microscopic images. This technique leverages interpretable taxonomic features based on the external geometric attributes ...
Added: September 21, 2026
Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1053–1060
This paper presents a novel approach to classification in biomedical imaging, specifically targeting polyp recognition in video endoscopy snapshots. Our method leverages specialized image descriptors to enhance the accuracy and robustness of polyp recognition. By employing these specialized descriptors, we address the challenges inherent in analyzing biomedical images from open datasets. Our approach not only ...
Added: September 21, 2026
Самарин А. В., Торопов А. Г., Савельев А. Г. et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 4 P. 1044–1052
This paper presents a study aimed at improving the detection quality of small-sized microorganisms under challenging microscopic conditions through the application of a lightweight combined image preprocessing model. We focused on the task of detecting diplococci in images obtained through dynamic sample microscopy. The proposed approach employs predefined filters for image preprocessing, combined with the ...
Added: September 21, 2026
Singapore: Springer Singapore, 2025.
Added: September 21, 2026
Tomat A., Sergei O. Kuznetsov, International Journal of Approximate Reasoning 2026 Vol. 197 Article 109754
Interval Pattern Structures (IPS) provide a natural way to represent local, human-readable explanations for predictions on numerical data through vectors of intervals interpreted as axis-parallel hyper-rectangles. In this paper, we develop and evaluate an IPS-based k-nearest neighbors classifier, IPS-KNN, that explains each prediction through a single local interval description rather than through the aggregation of ...
Added: September 21, 2026
Aleksei Samarin, Nazarenko A., Kotenko E. et al., / Series arXiv "math". 2025. No. 2511.20141.
This paper presents a novel approach to neural network compression that addresses redundancy at both the filter and architectural levels through a unified framework grounded in information flow analysis. Building on the concept of tensor flow divergence, which quantifies how information is transformed across network layers, we develop a two-stage optimization process. The first stage ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Pattern Recognition and Image Analysis 2025 Vol. 35 No. 2 P. 169–178
This study explores the incorporation of specialized self-attention mechanisms into deep learning architectures, with a particular emphasis on segmenting human iris and pupil regions in infrared images. In this work, we present some modified versions of nonlocal blocks designed to enhance self-attentive properties while addressing the distinct characteristics of infrared imaging data. By applying these customized ...
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 10 Article 359
Timely identification and accurate delineation of ultra-early ischemic stroke lesions in non-contrast computed tomography (CT) scans of the human brain are of paramount importance for prompt medical intervention and improved patient outcomes. In this study, we propose a deep learning-driven methodology specifically designed for segmenting ultra-early ischemic regions, with a particular emphasis on both the ...
Added: September 21, 2026
Springer, Cham, 2025.
Added: September 21, 2026
Aleksei Samarin, Alexander Savelev, Aleksei Toropov et al., Journal of Imaging 2025 Vol. 11 No. 6 P. 1–20
This study presents a unified low-parameter approach to multi-class classification of microorganisms (micrococci, diplococci, streptococci, and bacilli) based on automated machine learning. The method is designed to produce interpretable taxonomic descriptors through analysis of the external geometric characteristics of microorganisms, including cell shape, colony organization, and dynamic behavior in unfixed microscopic scenes. A key advantage ...
Added: September 21, 2026
I. D. Lazarev, Narozniak M., Byrnes T. et al., Physical Review A: Atomic, Molecular, and Optical physics 2025 Vol. 111 No. 012416 Article 012416
Unsupervised machine learning is one of the main techniques employed in artificial intelligence. We introduce an algorithm for quantum-assisted unsupervised data clustering using the self-organizing feature map, a type of artificial neural network. The complexity of our algorithm scales as 𝑂(𝐿𝑁), in comparison to the classical case which scales as 𝑂(𝐿𝑀𝑁), where 𝑁 is the ...
Added: September 14, 2026
Воронова К. Д., Lyadova L. N., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4 P. 153–170
Title: Automated Event Logs Generation Based on Unstructured Internet Sources for Process Analysis Tasks
Abstract. This paper presents an approach to automated structuring event-related information extracted from unstructured textual Internet sources for process mining tasks. In many practical cases, information on events associated with various processes is not presented in the form of ready-made event logs, but is ...
Added: September 14, 2026
Lebedev O. B., Левченко Д. Д., Черкасов Р. И., Инженерный вестник Дона 2026 № 2(134) Статья 7
This article analyzes the impact of artificial intelligence (AI) and machine learning technologies on the development and transformation of cyberthreats and the creation of highly effective cyberdefense systems. Key trends in AI evolution are discussed, including data-, model-, application-, and human-centric approaches, and their role in shaping both defensive and offensive capabilities. It is shown ...
Added: September 12, 2026
Lebedev O. B., Шмелева А. Г., Гежа Н. С., Информатика и автоматизация (Труды СПИИРАН) 2026 Т. 25 № 3 С. 720–750
This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...
Added: September 10, 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
Starodubov K., Гвасалия Г. В., Карасев П. И., Нано-био-технологии. Тепло- и электроэнергетика. Математическое моделирование: сборник статей III международной научно-практической конференции (Липецкий государственный технический университет, Липецк, Россия) 2025 С. 219–223
This paper discusses the concept of neural networks, convolutional neural networks, their architecture and their operation principle. The main attention is paid to testing the reliability of storing images of people as embeddings, which are considered to be unrecoverable in the original image. In the course of the research an experiment is carried out: the ...
Added: September 6, 2026