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October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Generalized Centrality Measures for Multiplex Networks: Combining Node Attributes and Group Dynamics

Procedia Computer Science. 2025. Vol. 266. P. 818–824.
Aleskerov F. T., Semenova A.

Many complex systems are best represented as multilayer or multiplex networks, where nodes are connected through multiple types of links across different layers. This layered structure introduces additional challenges for identifying central elements, as traditional centrality measures typically assume a single-layer network. The paper introduces a new centrality framework for multiplex networks that accounts for both vertex attributes and group-mediated influence, offering a refined approach to identifying critical nodes in multilayer systems. Additionally, we introduce a block concept, combining weights, node parameters, and inter-layer group effects into a unified analytical model. The model is applied to the Florence families dataset.

Research target: Mathematics
Language: English
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Keywords: centrality measuresмногослойные сетииндексы центральности в сетяхгрупповое влияние в сетяхgroup influence in multiplex networksmultiplex network centrality measures
Publication based on the results of:
Decision-Making in Socio-Economic, Political and Financial Spheres (2025)
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