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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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Математико-картографическое моделирование межрегиональных миграционных потоков в России

Известия Иркутского государственного университета. Серия: Науки о Земле. 2014. Т. 8. С. 133–144.
Timonin S., Тикунова И. Н., Штробл Й.

The paper is devoted to the detailed analysis of interregional migratory flows in Russia in 2000–2010 on the basis of the use of mathematic-cartographical models of migration. The investigation is aimed at application of mathematical and new GIS approaches for the development of forecasts of interregional migratory movements that is the extremely difficult task for both demographers and geographers. Results of modeling are included in the general forecasting models of size and structure of the population of Russian regions, and also will be used for management of migratory processes in Russia under conditions of general depopulation and reduction of its labor force. The detailed analysis of interregional migratory streams in Russia for 2000–2010 is carried out. For description and analysis of migratory processes, their subsequent interpretation and fore-  casting mathematic-statistical and mathematic-cartographical models of migration were used. Thus, accounting of spatial aspect turned out to be extremely important that demanded attraction of geographical, including geoinformation research methods. The new mathematical models necessary for description and forecast of migration which will be described below are developed. A series of maps reflecting migratory movements in 2000–2010, as well as the maps of dynamics is prepared. 

Priority areas: sociology humanitarian IT and mathematics
Language: Russian
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Keywords: миграции населениярегионы Россииmigration of populationregions of Russia mathematic-cartographical modelingматематико-картографическое моделирование
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