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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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Каузальный механизм vs нагромождение фактов? Критерии оценки причинно-следственных связей в case studies

Полис. Политические исследования. 2017. № 2. С. 134–146.
Turchenko M., Zavadskaya M.

This article speaks to methodological aspects of the ways to use a popular research technique – process tracing. The latter has gained momentum as a compromise between neo-positivist and interpretative approaches. Authors provide a brief overview of the method’s role in current political research; carefully describe the peculiarities of method’s procedure; compare process tracing with other research tools and discuss its advantages and shortcomings. Process tracing is a type of within-case analysis that aims at inferring causal mechanisms that bring about outcomes in question. The main strengths of the approach are 1) possibility of falsification tests, 2) rigor of analytical procedure, based on Bayesian logic and related empirical tests, 3) getting the most of in-depth knowledge of the case, 4) compatibility with quantitative research as the auxiliary method. Apart from that, process tracing serves as a powerful remedy against a-theoretical narratives and turns the case study into a genuinely captivating detective storyline. Among the weak points one should mention 1) lack of parsimonial explanations, 2) lack of generalizability, 3) time-consuming process of data collection. To demonstrate how process tracing can be used in real-world research the article provides one example based on study by Ahmed which devoted to electoral reforms in Europe at the end of the 19th century. It is shown how Ahmed based on process tracing falsified the influential theory by Rokkan-Boix and put forward the solid argument for her model of explaining the logic of electoral system reforms in Europe at the time of the franchise expanded.

Priority areas: humanitarian
Language: Russian
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Keywords: case studyкейс-стадиметодология политической наукиPolitical Methodologyqualitative analysisкачественный анализelectoral reformprocess tracingBayesian logiccausal mechanismprocess tracingбайесовская логикапричинно-следственный механизмэлекторальная реформа
Publication based on the results of:
Эволюция культур сквозь призму трансформации личностной мотивации (2017)
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