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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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Региональная дифференциация показателей человеческого потенциала

Экономика региона. 2015. № 4. С. 185–196.
Ulyanov V. V., Локосов В. В., Рюмина Е. В.
The purpose of the article is the interregional analysis of human potential. In comparison with the quality of life of the population, the quality of population itself is studied far less. The article presents an expanded characteristic of human potential in seven directions: economic activity, demographic processes, physical health, cultural potential, social health, educational potential and the attitude of the population to the environment. On the basis of statistics for 2008–2012 years, 63 indicators of human potential for all directions are selected. In the final result, the correlation analysis has led to the substantiation of the system of indicators consisting of 10 indicators. Three economic and seven social indicators characterizing human potential are included into this system. On the basis of the indicators by means of hierarchical agglomerative methods of cluster analysis, a classification of the Russian regions is carried out in two versions: with economic indicators and without them. The result of the calculations is a stable temporal typology of regions by indicators of human potential covering 74.4 % of the population of Russia. The article provides a substantial interpretation of dividing regions into groups, identifies the strengths and weaknesses of each cluster, shows the specific features of the regions included into the clusters. The obtained results can be used in the development of measures for the reduction of the interregional inequality in terms of human potential. It is possible to define what measures can be effective by studying the strategic directions of the development of regions in the cluster which is the most successful regarding the characteristics of human potential.
Priority areas: sociology
Language: Russian
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Keywords: человеческий потенциалcluster analysisкластерный анализчеловеческие ресурсыhuman resourceshuman potentialsocial indicatorsтипология регионовquality of populationtypology of regionsкачество населениясоциальные показатели
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