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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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Определение тенденций социально-экономического развития экономики Пермского края

Вестник ПНИПУ. Социально-экономические науки. 2018. № 2. С. 137–146.
Tretyakova E., Алфёрова Т. В.

The main socio-economic indicators of the Perm Krai for the period from 2005 to 2016 are analyzed
and the factors influencing their dynamics are revealed. The purpose of the study is to determine
the socio-economic development vector of Perm Krai economy. Methodical tools are systemic, logical
and statistical methods to analyze official information about national and regional socio-economic systems;
economic analysis methods to calculate fixed assets and labor efficiency use. The key conclusion
of the study is a clear reflection of the fact that the industrial sector of the Perm Krai economy is characterized
by an annual increase in labor productivity with a high degree of depreciation of fixed assets, on
the background of low real wage growth rates, which indicates the orientation of Perm labor market to
labor resources exploitation policy. The main results of the work include calculation and analysis of
labor costs return dynamics, return on capital and fixed assets per employee, which allows to conclude
that the labor resources consumption has the greatest influence on the aggregate product value created
in the process of production. The novelty of the work consists in a justified definition of the regional
economy development vector, based on economic analysis and comparison of its results with statistical
data. The obtained results should be taken into account when forming the concept of social and economic
development of the region, since with the maintenance of such a production structure, for further
growth of the Perm Krai economy, it is necessary to focus on social policy, including reproduction of
labor resources: increase of real wages, improvement of working conditions, quality of life, migration
outflow, population increase, etc.

Priority areas: economics state and public administration
Language: Russian
DOI
Text on another site
Keywords: производительность трудаlabor productivitycapital returnфондовооруженность
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