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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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?

Модернизация классической части квантового алгоритма Питера Шора

СПбГУ ИТМО, 2019.
Смирнов И. А., Разумов П. В., Короченцев Д. А., Поркшеян В. М., Черкесова Л. В.
Leading author: Л. В. Черкесова
Language: Russian
Full text
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Keywords: квантовый алгоритмП.Шор
Модернизация классической части квантового алгоритма Питера Шора
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Повышение быстродействия квантового алгоритма факторизации Питера Шора путём усовершенствования его классической части
Смирнов И. А., Черкесова Л. В., Разумов П. В. et al., Современные наукоемкие технологии 2019 Т. 1 С. 114–118
The proposed article compares the quantum factorization algorithm of Peter Shor and the factorization algorithm of the ?-John Pollard method. As is well known, the quantum algorithm for factoring Shor consists of classical and quantum parts. In the classical part, it is proposed to use the Euclidean algorithm to find the greatest common divisor of ...
Added: May 10, 2023
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