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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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New development: State-owned enterprises as powerhouses for innovation — the Russian case

Public Money & Management. 2016. Vol. 36. No. 4. P. 297–302.
Gershman M., Thurner T.

There have been many analyses of innovation in Russia’s state-owned enterprises (SOEs) and most conclude that the way forward requires the SOEs to transform into innovation powerhouses. Hence, in 2011, the Russian government set up an ambitious initiative to push innovation in the largest SOEs, which will run until 2020. This initiative has now begun its second phase. Using major case studies, for example Aeroflot and Russian Railways, this article examines the impact of the initiative. Understanding the Russian experience of transforming SOEs provides important lessons for many other emerging economies.

Priority areas: management
Language: English
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DOI
Text on another site
Keywords: Russiainnovationpublic policystrategystate-owned enterprises
Publication based on the results of:
Development of the new approaches to the analysis and modeling of the behavior of actors of innovation processes and markets: operationalization of innovation strategie (2016)
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