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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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?

Time series momentum: Evidence from the European equity market

Heliyon. 2023. Vol. 9. Article e12989.

This study empirically analyzes time series momentum (TSM) in the European equity market
between 2000 & 2020. The study produces additional evidence on TSM where a significant and
persistent market price anomaly enables investors to earn abnormal returns. To achieve this goal
the present study implements a pooled autoregressive model to test the predictability power of
European equity indices of future returns. The results indicate that strategies based on TSM are in
line with the discussed literature and enable market agents to earn returns above the market
(0.71% per month) by using a six-factor model.

Language: English
Full text
DOI
Text on another site
Keywords: autoregressionasset allocation Factor modelsTime series momentumPrice anomaly
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