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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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Health, Grades and Friendship: How Socially Constructed Characteristics Influence the Social Network Structure

P. 381–391.
Dokuka S., Krekhovets E., Priymak M.

Homophily - tendency for people to form social connections with similar others - is one of the key topics in social network analysis. It indicates to what extent people tend to be similar to their friends and in what dimensions. For the long time homophily was just an index of the social similarity, but for the recent years the interest for the homophily formation, dynamics and multidimensionality increased. In this paper we investigate the homophily in such social constructed behavior as food consumption and academic achievements. The study of body mass index in social network context reveals the presence of homophily, which means that persons with similar constitution are more likely to be interconnected with each other. Interestingly, that healthy food consumption has no impact on social network formation, but there is homophily based on fast food consumption. Thus, ‘bad habits’ are stronger forces for the social ties formation. This results show that social constructed behavior is an important component on the process of social network formation.

Language: English
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Keywords: social networksHomophilyacademic achievementshigher educationstudent networksHealth Food consumption
Publication based on the results of:
The Influence of Institutional Peculiarities of the Russian Higher Education Market on the Strategies of Professors and Students (2017)

In book

Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected Papers
Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected Papers
Vol. 10716. , Cham: Springer, 2018.
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