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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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Научно-техническая политика: глобальные тренды и практики

M. : ISSEK HSE, 2024.
Gershman M., Brambila F., Bredikhin S. V., Gokhberg L., Grebenyuk A. Y., Dimov G., Evseeva M., Ivanova E., Ivanova I., Klypin A., Kuznetsova T., Kutsenko E., Mamedyarov Z., Невская А. А., Ostashchenko T., Sabelnikova E. V., Svarchevskaya M., Tyurchev K., Kameneva E., Анташева М. С., Yavorskaya Y., Arzumanyan A., Gutaruk E. V., Лушачев Н. В.
Leading author: Gershman M.
Under the general editorship: Gokhberg L., Gershman M.
Compiler: Форысенкова Г. Е., Vasilyev O., Севоднева А. Г., Podzolkova Galina Vladimirovna G., Tsygankov I.

The report summarizes the results of a study of global trends in science and technology policy, modern strategies and practices in the field of science and technology, carried out by the Institute for Statistical Studies and Economics of Knowledge (ISSEK) of the National Research University Higher School of Economics in 2022-2023.

The current trends in global science and technology policy, identified using the iFORA big data mining intelligence system, are presented. An analysis of foreign practices of public administration in science and technology sphere, key strategic documents and specific initiatives developed by leading countries was carried out. Proposals have been prepared to improve the science and technology policy of Russia, taking into account the best international experience.

Research target: Political Science, International Relations, and Public Administration Economics and Management
Language: Russian
Full text
DOI
Keywords: science and technologyнаука и технологиигосударственная научно-техническая политикауправление наукойiFORAiFORAscience managementpublic policy in science and technology
Publication based on the results of:
Comprehensive scientific-methodological and information-analytical support for the development and implementation of state science, science and technology policy (2023)
Научно-техническая политика: глобальные тренды и практики
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