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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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Consequences of Schengen Visa Liberalisation for the Citizens of Ukraine and the Republic of Moldova

2012. No. 1.
Korneev O., Weinar A., Makaryan S., Mananashvili S.
This report asks one overarching question: “What impact would liberalisation of the visa regime produce on actual migratory movements between Ukraine and Moldova, and the EU?”. Therefore, we are not interested in assessing the mobility of tourists, but rather of migrants who work in the EU. This gives our study a specific perspective that looks at the Schengen visa regime as a tool of labour migration policy. We base our conclusions on primary and secondary qualitative data. We do not discuss here statistics but rather rely on the opinions and testimonies of experts, migrants and potential migrants. The first section of the report is a review of the most important public reports and studies of the impacts of EU visa policy on the mobility of Ukrainians and Moldovans. The second part, delineating current visa practices, is based on three types of data: the Delphi survey of experts conducted in December 2011 by the research team, qualitative interviews with Moldovan and Ukrainian migrants in Germany, Italy and Poland as well as interviews with potential migrants in Ukraine and Moldova, all conducted in the countries by our research colleagues; and a review of the legal framework performed by the research team. The content of the third section, focusing on forecasts, is derived from the same data sources as the second section and translates the results of our research into a set of recommendation and policy options.
Research target: Sociology (including Demography and Anthropology Law Political Science, International Relations, and Public Administration
Priority areas: sociology state and public administration law
Language: English
Full text
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Keywords: УкраинаUkraineMoldovaМолдоваШенгенмиграционный потенциалSchengenmigration potentialEU visa policyvisa liberalisationвизовая политика ЕСлиберализация визового режима
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