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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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Проблемы и перспективы развития российской аспирантуры: взгляд региональных университетов

Высшее образование в России. 2020. Т. 29. № 10. С. 9–28.
Terentev E., Бедный Б. И.

The concentration of state resources in the leading universities poses the problem of reproduction of the scientific and pedagogical personnel in regional universities that do not participate in state-funded academic excellence programs. Based on the data from three focus group interviews with heads of doctoral studies offices at regional universities, the article analyzes problems arising in the implementation of the current model of training and certification of doctoral students. Four following groups of problems are identified: 1) the rigidity of requirements for the structure and content of the educational programs, 2) the imperfection of the system of attestation, gaps between attestation activities, 3) the problem of “retention” of doctoral students after the completion of the educational program, 4) the problems of conjugation of the processes of preparing a dissertation and its defense. The authors discuss possible ways to overcome the identified problems through providing universities with greater autonomy in designing the structure and content of the educational programs; synchronization of the procedures of the final state attestation and dissertation defense; creation of mechanisms for supporting successful doctoral graduates at the final stage of their preparation for the defense of a dissertation; development of network forms for implementation of doctoral programs with leading universities and research institutes.

Priority areas: sociology
Language: Russian
Full text
DOI
Keywords: аспирантурарегиональные университетыuniversity networksуниверситетские сетиdoctoral educationregional universitiesэффективность аспирантуры state attestation of doctoral studentsefficiency of doctoral educationитоговая аттестация аспирантов
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