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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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The Impact of Institutional Quality on Manufacturing Sectors in Russia: Panel Data Analysis

2019.
Chernyavskiy A., Alexeev M.
We use the 2005-2012 data for Russian regions to show that higher regional institutional quality strongly benefits institutionally-dependent manufacturing sectors in terms of both gross output levels and growth rates. Unlike the existing literature on this topic, which uses cross-sectional or pooled specifications, we focus on panel data analysis. This approach mitigates endogeneity concerns and allows for calculating full marginal effects of institutions on manufacturing sectors with different degrees of institutional dependence. Our results imply that significant institutional improvements are needed in order for the Russian economy to diversify away from heavy reliance on oil and natural gas.
Priority areas: economics
Language: English
DOI
Text on another site
Keywords: specificityrelationshipinstitutional quality
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