Скрытые марковские модели и MPS-временные ряды

З. И. Бежаева; Олехова Е. Ф.; Оселедец В. И.

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July 24, 2026

'Physics Is What the World Is Literally Built On'

Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.

July 20, 2026

Scientists Create Open Dataset for Studying Concentration

A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.

July 20, 2026

‘Science Is Universal-It Knows No Borders

Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

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Скрытые марковские модели и MPS-временные ряды

С. 89–95.

Bezhaeva Z., Олехова Е. Ф., Оселедец В. И.

In the paper consider explicit exemple of MPS time series and its cjnnection with hidden markov processes

Language: Russian

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Keywords: Matrix product state hidden markov processes MPS-модели Скрытые марковские временные ряды

In book

Материалы конференции «Современная математика и концепции инновационного математического образования»

М.: ООО "Издательский дом МФО", 2014.

A Clustering Model for Stocks that Considers Hidden Dynamics and Price Trajectory

Morychev G., Sizykh D., Sizykh N., IEEE Access 2025 Vol. 13 P. 213194–213210

One of the main tools for analyzing large volumes of financial data is the use of clustering methods and models, which allow the identification of various patterns. This study examines the problem of clustering time series that reflect the behavior of prices, yields, modes, trends, and a number of related stock indicators. The relevance and ...

Added: February 3, 2026

Low-rank Riemannian eigensolver for high-dimensional Hamiltonians

Rakhuba Maxim, Novikov A., Oseledets I., Journal of Computational Physics 2019 Vol. 396 P. 718–737

Such problems as computation of spectra of spin chains and vibrational spectra of molecules can be written as high-dimensional eigenvalue problems, i.e., when the eigenvector can be naturally represented as a multidimensional tensor. Tensor methods have proven to be an efficient tool for the approximation of solutions of high-dimensional eigenvalue problems, however, their performance deteriorates quickly ...

Added: October 19, 2020