Výsledky vyhledávání - "A. Sokolovskiy"

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Machine Learning algorithms for optimization of magnetocaloric effect in all-d-metal Heusler alloys

Autor: Baigutlin, Danil, Sokolovskiy, Vladimir, Buchelnikov, Vasiliy, Taskaev, Sergey

This study examines the application of machine learning algorithms, specifically the Random Forest regression model, to optimize the magnetocaloric effect in all-d-metal Heusler alloys. The model was trained using descriptors related to the mean prop

Externí odkaz: http://arxiv.org/abs/2409.14370

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Early warning systems for financial markets of emerging economies

Autor: Kraevskiy, Artem, Prokhorov, Artem, Sokolovskiy, Evgeniy

We develop and apply a new online early warning system (EWS) for what is known in machine learning as concept drift, in economics as a regime shift and in statistics as a change point. The system goes beyond linearity assumed in many conventional met

Externí odkaz: http://arxiv.org/abs/2404.03319

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Akademický článek

The PAZ polarimetric radio occultation research dataset for scientific applications

Autor: R. Padullés, E. Cardellach, A. Paz, S. Oliveras, D. C. Hunt, S. Sokolovskiy, J.-P. Weiss, K.-N. Wang, F. J. Turk, C. O. Ao, M. de la Torre Juárez

Publikováno v: Earth System Science Data, Vol 16, Pp 5643-5663 (2024)

Polarimetric radio occultations (PROs) represent an augmentation of the standard radio occultation (RO) technique that provides precipitation and cloud vertical information along with the standard thermodynamic products. A combined dataset that conta

Externí odkaz: https://doaj.org/article/c5729215cda94e3394cb1b1b75ea04df

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Akademický článek

The Influence of the Cultural and Religious Factors on the Media

Autor: Khudarova, Anastasiya, Abdramanov, Yerbol, Tsvetkova, Milena, Sokolovskiy, Konstantin

Publikováno v: Journal of Ethnic and Cultural Studies, 2024 Jan 01. 11(3), 114-137.

Externí odkaz: https://www.jstor.org/stable/48793994

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Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust

Autor: Erlygin, Leonid, Zholobov, Vladimir, Baklanova, Valeriia, Sokolovskiy, Evgeny, Zaytsev, Alexey

Machine learning models play a vital role in time series forecasting. These models, however, often overlook an important element: point uncertainty estimates. Incorporating these estimates is crucial for effective risk management, informed model sele

Externí odkaz: http://arxiv.org/abs/2302.02834

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