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News
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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Econometric analysis of factors of internal migration in Russia

Regional Research of Russia. 2016. Vol. 6. No. 4. P. 344–356.
Vakulenko E.

The article analyzes internal migration in Russia and identifies the main factors that influence it. The model of migration factors is estimated from panel data on Russian regions based on official Rosstat data for 1999–2010. Demographic factors, indicators of the labor market and housing, quality of life, the provision of public goods, infrastructure, and expenditures from regional consolidated budgets on various needs are considered as migration factors. Analysis showed that migration sensitivity is higher to demographic and economic factors (housing provision and per capita income), rather than to different social or other factors. Expenditures on education and healthcare in regions have the biggest impact on migration among all other regional budget expenditures.

Research target: Economics and Management
Priority areas: economics
Language: English
Full text
DOI
Keywords: социальная политикамиграцияпанельные данныеsocial policymigrationpanel dataроссийские регионы Russian regions
Publication based on the results of:
Taking into account heterogeneity of Russian economy’s branches under modelling of their dynamics (2016)
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