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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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Разработка и применение комплексных нейросетевых моделей массовой оценки и прогнозирования стоимости жилых объектов на примере рынков недвижимости Екатеринбурга и Перми

Имущественные отношения в Российской Федерации. 2017. Т. 186. № 3. С. 68–84.
Yasnitsky L., Ясницкий В. Л.

Developed complex economic and mathematical models of mass valuation of residential real estate of cities of Yekaterinburg and Perm, which take into account both construction and operating parameters of the apartments, and the changing economic situation in the country and the world. Study models showed that the increase in new housing in Yekaterinburg, 4% in the short term can lead to market saturation and the subsequent decrease in the value of residential properties, in contrast to the Perm market, where the increase of housing to the same 4% to the saturation effect of the market does not.

Research target: Mathematics Economics and Management
Priority areas: economics management business informatics
Language: Russian
Full text
Keywords: недвижимостьоценка недвижимостипрогнозированиеartificial neural networks real estateискусственная нейронная сетьestate appraisal
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Semi-Interlaced Polytopes
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Мотивы распределения суверенного финансирования в Евразийском регионе: пример USAID и АБР
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Added: June 11, 2026
Assessing the impact of economic sanctions on the socio-economic development of a sanctioned country -testing a new research approach using the data on the socio-economic development of Russia in 2022-2025
Gurkov I. B., Kossov V. V., Filinov N. et al., / NRU Higher School of Economics. Series MAN "Management". 2026. No. N/A.
This research note is devoted to assessing the socioeconomic impact of sanctions of sanctioned countries and uses the data on Russia in 2022-2024. We use for the analysis four fundamental socioeconomic parameters-the expected length of life of males at birth, the misery index (Okun's index), the level of Gross Domestic Product at purchasing parity prices, ...
Added: June 11, 2026
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