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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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?

Пространственно-временная динамика эволюционных процессов в сложных системах

Гл. 4. С. 185–217.
Knyazeva H., Куркина Е. С.

The evolutionary model elaborated by Sergei P. Kurdyumov is considered in the article. Some key ideas put forward by him constitute a basis for development of the methodology of sudy of complex selforganizing systems, called also synergetics. Four important theoretical notions form a fundament of this evolutionary model: connection between space and time, complexity and its nature, blow-up regimes, in which self-organization and rapid, avalanche-like growth of complexity occur, evolutionary cycles and switching of different regimes as a necessary mechanism for maintenance of “life” of complex structures. The methodology allows to understand the nature of innovative shifts in nature and society and to show a possibility of management of innovative processes and of construction of desirable future. Some approaches for possible application of this model for understanding of dynamics of complex social, demographic and geopolitical system are discussed.

Language: Russian
Keywords: самоорганизацияinnovationсинергетиканелинейностьnonlinearityсложные системыинновацияконструирование будущегоself-organizationsynergeticscoevolutionкоэволюцияspace and timetempo-worldscomplex systemsblow-up regimeрежим с обострениемтемпомирпространство и времяinstabilityconstruction of the futureнеустойчивость

In book

Инновационная сложность
Инновационная сложность
СПб.: Алетейя, 2016.
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