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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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Перспективы применения систем мониторинга логистических показателей функционирования производственных предприятий

Логистика и управление цепями поставок. 2018. № 6(89). С. 129–136.
Петровский Д. В., Барашков А. В.

This article discusses perspectives of the use of monitoring systems
in the enterprises of the manufacturing sector of logistics. The
case for the implementation of such systems on real production facilities
was considered. The economic efficiency of using monitoring
systems was analyzed. For this, three scenarios were created under
which it is possible to make mistakes when performing the business
process of determining the need for inventory items. The first
of them described a situation in which the time of error detection was
1 day; the second scenario suggested an increase in the time of failure
to 2 days; scenario 3 described the use of the real-time monitoring
system and described situation in which failure in the supply
chain caused by shortage of goods was determined instantly. After
that, these scenarios were analyzed on the basis of existing contract
for production of certain number of finished products. It is shown
that the monitoring system can significantly reduce batch production
time due to a significant reduction in the probability of making
mistakes. Finally, it was shown how the implementation of monitoring
and automation system for a number of tasks affects the efficiency
of business processes.

Priority areas: economics
Language: Russian
Keywords: бизнес-процессыинтеграцияintegrationmonitoring systemсистема мониторинга business processfailures in logistics systemsсбои в логистических системах
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