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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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Towards an Open Government Data Comparative Model

P. 344–351.
Styrin E. M., Sandoval R.

Governments around the world have been increasing their practices for open government data (OGD). After the launch of the initiative for the Open Government Partnership (OGP) many countries have developed legal arrangements, organizational transformations and cultural challenges in order to implement some practices of OGD in their Public Administrations. However very few have compared their results and experiences in a systematic way. The purpose of this paper is to introduce a first step to develop a comparative framework of OGD. Using the experience of Mexico and Russia governments on implementation we describe this experience of country comparison in order to foster the OGD implementation across the world

Language: English
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Keywords: РоссияМексикаRussiaОткрытое правительствоopen governmentмежстрановые сравнительные исследованияopen dataоткрытые данныеcomparative studyMexico

In book

Proceedings of The 11th International Conference on Theory and Practice of Electronic Governance (ICEGOV2018)
Styrin E. M., Sandoval-Almazan R. NY: ACM Press, 2018.
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