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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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О социальной проницаемости границ муниципальных образований

Региональные исследования. 2021. № 1 (71). С. 34–45.
Yashunsky A.

The article investigates the intensity of social interaction between the population of different municipalities in Russian Federation. This interaction is estimated using user profile data from online social networks: a data source that grows more and more popular in population geography studies. We build a qualitative indicator of social interaction using data on the number of interregional friendship links for «VKontakte» social network users that live in different municipalities and have an open social network profile. We show that the intensity of social interaction is higher on the average for municipalities that share a common border. Social interaction intensity data is then used to characterize the permeability of municipality borders. We choose the least permeable borders among all border segments of municipalities in Russian Federation: those with the smallest transborder interaction intensity values and describe the social barriers that are revealed this way. We describe various configurations of these barriers and suggest hypotheses for the reasons why such barriers appear or donot appear. We also analyze several groups of socially insular groups of municipalities in the Khanty- Mansi Autonomous Okrug and the Yamalo-Nenets Autonomous Okrug and suggest possible reasons for their insularity.

Priority areas: management state and public administration
Language: Russian
Full text
DOI
Keywords: социальные сетимуниципальные образованияsocial networksграницаmunicipalitiesмежрегиональное взаимодействиеneighborhoodобособлениеsocial proximityinterregional interactions borderborder permeabilityinsularityсоциальная близость соседствопроницаемость границ
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