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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
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HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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Possibility of Recovering Message Segments Based on Side Information about Original Characters

Doklady Mathematics. 2024. Vol. 108. No. 2. P. S282–S292.
Malashina A.

To provide secure information exchange in communication channels, the correctness of the operation of the relevant information protection systems must be preliminary studied. The mathematical algorithms used in such systems are correct and can theoretically provide the correct statistical properties of the output stream compared to the input. However, at the stage of implementation (programming) of these protection algorithms or at the stages of assembling the final equipment (using hardware, making adjustments) and its operation in real conditions, it is possible to introduce distortions that violate the operation of certain elements of information security tools (for example, a random number generator). As a result, by the nature of the transmitted signal, it becomes possible to determine that the output stream for a number of characteristics is steadily different from the ideal encrypted stream, which in theory should have come from the equipment and appeared at the output of the communication channel. In this situation, it is necessary to understand how the introduction of certain distortions affects the degree of security of the system being created. For this purpose, the parameters of various message sources are described, which simulate receiving an output stream with distortions. At the same time, the degree of security of the corresponding communication channel is proposed to be determined by estimating the proportion of the input stream that can be restored from the output using side information resulting from the introduction of appropriate distortions in the operation of the system.

Research target: Mathematics Computer Science
Language: English
DOI
Keywords: cryptographyShannon entropystream cipherscryptanalysisdictionary attack
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