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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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Proceedings of the PME and Yandex Russian conference: Technology and Psychology for Mathematics Education

M. : SU HSE Publishing House, 2019.
Under the general editorship: A. Shvarts

Proceedings of the Moscow regional conference of The International Group for the Psychology of Mathematics Education (PME) and Yandex are presented.

Chapters
Relationship between teaching practices and mathematical processes outcomes in secondary school: based on a longitudinal TIMSS-PISA study
Larina G., Kapuza A., , in: Proceedings of the PME and Yandex Russian conference: Technology and Psychology for Mathematics Education.: M.: SU HSE Publishing House, 2019. P. 278–278.
The competence of mathematical modelling is well conceptualized, thought a much-debated question is how to develop it in schools. International achievement test PISA consider mathematics achievements from the modelling perspective (formulating, employing and interpreting), and provides us with comprehensive data to analyze school factors in math results from the comparative perspective. The goal of our ...
Added: February 5, 2020
Functional investigation of the networks and white matter substrates associated with the processing of mathematical operations
I.S. Matiulko, S.P. Kulikova, K.V. Konopkina et al., , in: Proceedings of the PME and Yandex Russian conference: Technology and Psychology for Mathematics Education.: M.: SU HSE Publishing House, 2019. P. 280–280.
Processing of mathematical operations and solving numerical tasks implicate a distributed set of brain regions. These regions include the superior and inferior parietal lobules that underlie numerical processing such as size judgments, and additional prefrontal regions that are needed for formal mathematical operations such as addition, subtraction and multiplication [Arsalidou, Taylor, 2011]. Critically, little is ...
Added: January 13, 2020
Mathematical problem solving: behavioral and neuroimaging studies
K.V. Konopkina, I.S. Matiulko, M. Arsalidou, , in: Proceedings of the PME and Yandex Russian conference: Technology and Psychology for Mathematics Education.: M.: SU HSE Publishing House, 2019. P. 277–277.
The current study has three components: (a) a functional magnetic resonance imaging (fMRI) meta-analyses of past literature on mathematical operations; (b) a behav- ioral study to validate a math protocol with parametric changes in the difficulty of math problems that use addition, subtraction, multiplication and division; and (c) an fMRI study that examines the brain ...
Added: December 10, 2020
Learning intransitivity: from intransitive geometrical objects to "rhizomatic" intransitivity
Poddiakov A., , in: Proceedings of the PME and Yandex Russian conference: Technology and Psychology for Mathematics Education.: M.: SU HSE Publishing House, 2019. P. 178–185.
Added: January 3, 2020
Research target: Education Psychology Mathematics
Priority areas: mathematics
Language: English
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DOI
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Keywords: математическое образованиепсихология образованияEducational psychologymathematical education
Proceedings of the PME and Yandex Russian conference: Technology and Psychology for Mathematics Education
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