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  • Влияние пандемии COVID-19 на социально-экономическое развитие стран
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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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Влияние пандемии COVID-19 на социально-экономическое развитие стран

С. 544–551.
Богданова Т.К., Кравченко Т.К.

The economic development of a country is one of the main factors that characterize the state of the state, determining the dynamics of its development and position at the international level. During 2019 -2020, a pandemic of coronavirus infection was recorded in the world, which claimed millions of human lives and caused significant damage to the socio-economic development of countries.

The paper analyzes how restrictive measures taken by governments of different countries during the COVID-19 pandemic affected the socio-economic development of these countries. An approach to assessing the severity of the measures taken on the basis of cluster analysis is proposed and a comparative analysis of changes in the main socio-economic indicators under the restrictive measures taken by governments is carried out.

The analysis of the obtained results allows us to conclude that the degree of change in the analyzed indicators was affected not only by the already existing socio-economic situation in the countries, but also had a significant impact on the restrictive measures and the degree of their severity, which were undertaken by the government of each country to combat the spread of COVID-19 coronavirus infection.

Language: Russian
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DOI
Text on another site
Keywords: coronavirus infectionThe impact of pandemic COVID-19socio-economic development of countriesseverity indexsocio-demographic indicatorsВлияние пандемии COVID-19социально-экономическое развитие странкороновирусная инфекцияиндекс строгости мерсоциально-демографические показатели

In book

Системное моделирование социально-экономических процессов: труды 46-ой международной научной школы-семинара, г. Уфа, 9 - 15 октября 2023 г.
Воронеж: Истоки, 2024.
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