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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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Cтатистика креативной экономики в России

Экономические и социальные проблемы России. 2022. № 4(52). С. 61–76.
Nikolayenko E., Smirnov S. N.

The creative economy and its components – creative industries have recently attracted more and more attention of researchers. The development of indicators to assess its size, demand for its products and services, as well as its results, is one of the urgent problems. Currently, such indicators are not approved by regulatory and legal acts, and therefore researchers search for sources of information to develop appropriate indicators based on them. The authors analyze the possibilities of using such sources and present quantitative assessments based on cultural institutions, many of which contribute to the creative economy (for example, museum activities concerning historical and cultural heritage are officially classified as creative industries in the Russian Federation

Research target: Other Humanities
Language: Russian
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Keywords: государственная статистикаРоссиякреативная экономикаRussiaofficial statisticsучреждения культурыcreative industriesкреативные индустрии cultural institutions creative economy
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