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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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Clustering or Co-Agglomeration? A Love-for-Variety Approach

2016. No. WP BRP 140/EC/2016.
Malykhin N. I., Ushchev P.
We develop a simple partial-equilibrium model of endogenous city structure formation. No production externalities are at work, the only two forces shaping the spatial configurations of the city being love for variety (on the consumer side) and seeking for a better access to the market (on the firm side). We show that, unlike in existing models of a similar nature, our model generates clustering rather than co-agglomeration. Namely, if there are few firms relative to the urban population size, then firms tend to cluster at the city center, while consumers choose to reside on the outskirts. Otherwise, the opposite holds. Although a continuum of equilibrium city structures may emerge, we show that all spatial equilibria are segregated. In addition, the market outcome features spatial price dispersion, even though our framework does not involve imperfect information and search costs on the consumer side.
Research target: Economics and Management
Language: English
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Keywords: monopolistic competitionurban structure
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