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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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Геометрический подход к филогеографическому анализу молекулярных последовательностей: главные компоненты и дендрограммы

Молекулярная биология. 2023. Т. 57. № 2. С. 178–184.
Ефимов В. М., Efimov K., Ковалева В. Ю.

Currently, the search for manifestations of selection under the influence of the environment in molecular sequences is usually carried out within closely related species or at the intraspecific level. It is believed that at high taxonomic levels this is unpromising due to phylogenetic relationship. Cytochrome b amino acid sequences of 67 rodent and lagomorph species with known geographic coordinates were digitized using the AAindex database. Based on more than 200 thousand characters, the principal components were obtained. A well-known statistical method, which has not been previously used for such problems, was used, which makes it possible to orthogonally decompose multidimensional variability into intra- and intertaxon variability and analyze them separately. The subfamily level was selected. For the second principal component (17.05% of intertaxon variability), a correlation with latitude was found (r = 0.561; n = 67; p < E-5). The clear division into two groups, revealed by the first principal component (39.48% of intertaxon variability), which does not coincide with the taxonomic one, indicates a possible physicochemical underlying cause for the differences between them. This requires further research.

Research target: Biology Mathematics
Language: Russian
DOI
Text on another site
Keywords: кластерный анализевклидовы расстоянияортогональное разложениегеографические координаты
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