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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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Благоустройство городской среды и методы его оценки

Вопросы государственного и муниципального управления. 2025. № 3. С. 95–120.
Галкина А. Д., Plusnin J.

The article explores three approaches to assessing the level of urban environment improvement. In line with strategic planning tasks introduced by the Russian Government a decade ago, efforts to enhance the quality of life and the urban

environment quality have been guided by the theory of data-centric public administration. These efforts have been operationalized through composite indices developed by the Ministry of Construction of the Russian Federation and Vnesheconombank (the Ministry of Construction and VEB indices). The article provides a critical review of these tools employed since 2018. Two indices lack mutual comparability and complementarity: the Ministry of Construction index adopts a city-centric and spatially oriented perspective, focusing on the quality of the urban environment, while the VEB index is human-centric and primarily targets quality of life assessment. The authors propose an alternative methodology for evaluating urban environment improvement, grounded in an original conceptualization of well-being. At the core of this approach lies the idea of «good» as a dual-state concept, representing both the expected condition (well-being) and the achieved condition (urban improvement). Based on this framework, a new composite index has been developed to measure improvements in the urban environment. A key advantage of the proposed methodology lies in its practical simplicity and the intuitive clarity of its indicators for local residents. It is particularly well-suited for adoption by local governments in small towns and settlements as a tool for independent assessment

Research target: Political Science, International Relations, and Public Administration Economics and Management Sociology (including Demography and Anthropology
Language: Russian
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DOI
Text on another site
Keywords: благополучиекачество городской средыгородское благоустройствосоучаствующее проектированиеParticipatory designurban environment quality well-beingMinistry of Construction indexurban environment improvementurban environment improvement conceptVnesheconombank-indexиндекс МинстрояВЭБ-индексконцепция благоустройства среды обитания
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