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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Исследование возможности классификации фондовых рынков различных стран с помощью сетевой модели

Вестник Воронежского государственного университета. Серия: Системный анализ и информационные технологии. 2016. № 3. С. 111–115.
Vizgunov A. N., Наумова А. С.

The globalization process makes all countries stock markets similar to each other. In the paper we try to evaluate this process by analyzing the network models of some countries stock markets by means of neural networks. Our results show that each of the considered countries stock market has a peculiarity that can be used to distinguish the markets. 

Priority areas: IT and mathematics business informatics
Language: Russian
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Keywords: фондовый рынокглобализацияglobalizationнейронные сетиneural networksMarket network modelсетевая модельstock market
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