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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.
June 5, 2026
‘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.
June 5, 2026
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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Порог наступления старости: объективные признаки и субъективное восприятие

Народонаселение. 2023. Т. 26. № 3. С. 131–143.
Антонов А. И., Nazarova I. B., Карпова В. М., Ляликова С. В.

Population aging is a demographic trend characteristic of most world countries, it
requires attention from various social institutions. The situation of the growing number of older
people around the world increases the relevance of studying this issue. The article aggregates
data from different sources that determine the boundaries of the onset of old age based on various theoretical and methodological approaches. It also shows the proportion of old people in the
demographic structure of the Russian population in accordance with the chosen approaches. It is
shown that the most popular age of the onset of old age, reflected in theoretical concepts, is within
the range of 60–65 years. The article presents the results of the authors’ study, which covered 1198
respondents from more than 65 regions of the Russian Federation (organized by Lomonosov Moscow
State University together with ISESP FCTAS RAS in 2022). During the analysis of the data obtained,
some inconsistencies were found between the boundaries fixed in scientific discourse and the ideas
of the study participants about the moment of the onset of old age. The results obtained showed the
absence of significant differences in ideas about the moment of old age for men and women (69.4 and
68.0 years, respectively). There is a tendency to postpone the age of old age with an increase in the
age of respondent. A correlation between the actual and psychological age of old age showed that
“premature” aging (when a person recognizes himself as old, before he exceeds the age of old age he
named) is found in more than half of the respondents who associate themselves with older people.

Research target: Sociology (including Demography and Anthropology
Language: Russian
DOI
Text on another site
Keywords: старостьвозрастная структура населенияage structure of the populationold ageelderly peopleпожилыеpopulation aging
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