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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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Налоговые инструменты стимулирования инноваций в странах ЕС

Мировая экономика и международные отношения. 2023. Т. 67. № 3. С. 20–32.
Rastvortseva S., Панина Е. В., Кочешков М. А.

Solow–Swann’s neoclassical theory of economic growth shows that without technological progress, capital accumulation can only lead to a short-term increase in the growth rate of output per capita. The challenges of sustainable innovative development in many countries are coming to the fore today. The creation, dissemination and use of innovations occur in companies, universities, scientific organizations (micro-level), between economic entities within the framework of regional (meso-level) and national (macro-level) innovation systems, as well as at the international level. Innovation support is carried out at the meso-level, focuses on companies and organizations, and is evaluated at the level of the country as a whole. State support for innovation is necessary for the following reasons: 1) the ease of information transfer puts manufacturing companies in a less favorable position compared to consumer companies; 2) the difficulty of obtaining a loan for R&D with the risk of information leakage and lack of confidence in the final results; 3) the socio-economic system of the country receives more benefits from innovation than all companies in the aggregate. The article discusses such types of support as government subsidies and grants, tax incentives, measures for the development of human capital in an innovative environment, competition and intellectual property protection policy. In the international practice of stimulating innovation, tax incentives are used, (1) allowing to reduce R&D costs, (2) based on non-reduction of R&D expenditures and (3) preferential tax regimes derived from innovation activities. It is shown that the methodological approaches used to assess the effectiveness of tax measures are the B-index (calculated and published by the OECD by country), the analysis of the validity of tax instruments and the use of the European Tax Analyzer model – computer modeling. The analysis of innovative development showed that the European Union in terms of the number of patents, residents and non-residents, the share of researchers in the total population and the share of R&D expenditures in GDP for 2000–2022 is often inferior to China, the USA, Japan and Korea, but generally has a positive development trend. The most popular tools in the European Union countries are tax deductions, “super deductions”, R&D grants and other incentives. There is no direct correlation between the number of benefits and the level of innovation development. At the same time, it is noticeable that countries using a large number of support tools are becoming attractive to innovative companies and entrepreneurs. The article analyzes the measures of state support for R&D during the COVID-19 pandemic. Of these, the most relevant are grants and subsidies, and tax benefits. The analysis of tax instruments for stimulating innovation carried out in the article may be useful in the implementation of appropriate policies in other countries.

Research target: Economics and Management
Language: Russian
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Keywords: инновационное развитиеEuropean Unionналоговые льготыinnovationsналоговые инструменты innovative developmenttax deductionsгосударственная поддержка инновацийTax Creditstate support tax incentivespreferential tax regimesналоговый кредитстраны Европейского союза
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