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June 5, 2026
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
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Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

 

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On dissipativity of linearized 1d quasi-gasdynamic system of equations and its difference approximation for general equations of state

Lobachevskii Journal of Mathematics. 2025. Vol. 46. No. 11. P. 5718–5731.
A. Zlotnik, T. Lomonosov

We deal with the 1D quasi-gasdynamic (QGD) system of equations and a two-level explicit in time and three-point symmetric in space conservative difference scheme that approximates it, in the case of general equations of state.
Both the QGD system and scheme are linearized at any constant background solution (with non-zero or zero velocity). Matrices of their convective and dissipative terms are the same, and after respective scaling, they both become symmetric and depend mainly on the background ``signed'' Mach number and the ratio of the specific heats as well as the QGD parameters. Moreover, their form is almost the same as in the previously studied basic particular case of the perfect polytropic gas. This allows us to extend results on $L^2$-dissipativity of the QGD system and the scheme to the general case.
 

Research target: Mathematics Computer Science
Language: English
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Keywords: linearization 1D gas dynamics equationsquasi-gasdynamic regularizationexplicit difference schemegeneral equations of state$L^2$-dissipativity
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