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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.
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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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Ancient Greek Polis: From Homoarchy to Heterarchy and Back Again

Ch. 2. P. 33–52.
Ivan A. Ladynin

The chapter considers the historical development of the Ancient Greek city-state (polis) viewed through the categories of homoarchy and heterarchy basic for the present monography. The author traces its formation on the base of the homoarchical society of the Dark Ages, the peculiarities of its heterarchical structure, the background of its crise in the 4th century B.C.

Language: English
Full text
Keywords: heterarchyгетерархияантичный полисAncient GreeceДревняя ГрецияCity-Statehomoarchyгомоархия

In book

Principles and Forms of Sociocultural Organization: Historical Contexts of Interaction
Principles and Forms of Sociocultural Organization: Historical Contexts of Interaction
Gleb V. Aleksandrov, Bondarenko D. M., Anna K. Aleksandrova, Bovykin D., Valentina N. Burkova, Marina L. Butovskaya, Fedonnikov N., Sergey V. Kostelyanets, Ivan A. Ladynin, Marey A. V., Aleksei S. Shchavelev, Andrey V. Tutorski, Vdovchenkov E. L., NY: Anthem Press, 2026.
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