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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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Dynamics in a phase model of half-center oscillator: Two neurons with excitatory coupling

Communications in Nonlinear Science and Numerical Simulation. 2022. No. 104. Article 106045.
Korotkov A., Levanova T., Zaks M., Maksimov A. G., Osipov G.

A minimalistic model of the half-center oscillator is proposed. Within it, we consider dynamics of two excitable neurons interacting by means of the excitatory coupling. In the parameter space of the model, we identify the regions of dynamics, characteristic for central pattern generators: respectively, in-phase, anti-phase synchronous oscillations and quiescence, and study various bifurcation transitions between all these states. Suggested model can serve as a building block of specific complex central pattern generators for studies of rhythmic activity and information processing in animals and humans.

Research target: Mathematics Physics
Language: English
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Keywords: бифуркацииbifurcationshalf-center oscillatorcentral pattern generatortheta-neuronin-phase spikinganti-phase spikingсинфазная активностьпротивофазная активностьтета-нейронгенератор центрального ритмаполуцентр
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