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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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Моделирование связи депозитов и кредитов в российских банках — эконометрический подход

Финансы и бизнес. 2023. Т. 19. № 3. С. 86–99.
Kopnova E., Османова А. О.

According to the monthly data of the eleven largest banks in Russia for 2015-2020, the dynamic relationship between deposits of individuals and loans issued has been investigated. We used econometric tools for analyzing the cointegration of random processes in the form of an error correction model estimated from panel data. It is shown that the classical assumption about the independence of decisions in the deposit and credit markets is not fulfilled for Russian banks - both long-term and short-term relationships between them are found. The strict exogeneity of deposits in relation to the parameters of the model of their connection with loans was revealed. The conclusion is made about the inefficiency of the central bank's decisions on the monetary market in the period under review to ensure economic growth.

Research target: Economics and Management
Language: Russian
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Keywords: банкипанельные данныеbanksкредитыbank loansdepositsдепозитыпанельная коинтеграциямодель коррекции ошибкамиpanel cointegration modelvector error correction model panel data
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