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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.
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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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Initial stage of the O2 adsorption on Ag(100): vacancies and local oxide formation

Physical Chemistry Chemical Physics. 2026. Vol. 28. No. 1. P. 47–51.
B.V. Andryushechkin, Павлова Т. В., В.М. Ш., Нартова А. В., Бухтияров В. И.

The early stage of molecular oxygen adsorption on the Ag(100) surface was reexamined with scanning tunneling microscopy (STM) and density functional theory. Using an oxygen-functionalized STM tip, we demonstrated that the simple interpretation of the individual objects randomly distributed over the surface as chemisorbed oxygen atoms is incompatible with the cross-shaped structures observed in atomic-resolution images in the current work. In our model, each feature is an oxide-like cross formed by two intersecting O–Ag–O–Ag–O chains, with oxygen atoms in vacancies in the Ag(100) layer. Furthermore, we found numerous oxygen-free vacancies randomly diffusing over the surface under the STM probe even at 77 K.

Research target: Physics Chemistry
Language: English
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Keywords: vacanciessilverOxygenScanning tunneling microscopy (STM)
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