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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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Research on monolayer h-BN cell strain effect vacancy stability

Journal of Physics: Conference Series. 2019. No. 1353. Article 012020.
Serzhantova M. V., Titov M. A., Obvertkin I. V.

This article presents a research on Hexagonal Boron Nitride (h-BN) monolayer cell strain effect 2 % and 4 %. Structure of h-BN with nitrogen vacancy, with boron vacancy and with divacancy was considered for this. The calculations were carried out within framework of the density functional formalism with gradient corrections and using the VASP package. Vanderbilt Ultra-Soft Pseudopotential was used in the course of the calculations. It is possible to conclude that nitrogen vacancies are the most stable, regardless of monolayer deformation on the results obtained. Understanding of atomic scale stability and dynamics of defects in such systems is crucial for predicting their properties and applications in electronics.

Research target: Computer Science Physics
Language: English
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DOI
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Keywords: VASPDensity functional theory (DFT)h-BN
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