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  • Влияние электрической связи на динамику ансамбля нейроноподобных элементов с синаптическими тормозящими связями
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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.
June 5, 2026
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
Polina Tabakova decided to apply for a Philology degree at HSE in Nizhny Novgorod because she grew up in Mari El and did not want to move far away from the Russian forests. In an interview for the Young Scientists of HSE University project, she spoke about the genre of the campus novel, the existential drama of Kolobok, and a blackout version of Eugene Onegin.
June 5, 2026
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
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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Влияние электрической связи на динамику ансамбля нейроноподобных элементов с синаптическими тормозящими связями

Известия высших учебных заведений. Прикладная нелинейная динамика. 2018. Т. 26. № 5. С. 101–112.
Kazakov A., Леванова Т. А., Коротков А. Г., Осипов Г. В.

The phenomenological model of an ensemble of three neurons which are coupled by
chemical (synaptic) and electrical couplings is studies. A neuron is modeled by the oscillator of van
der Pol. The aim of work is a study of the influence of coupling’s strength and frequency detuning
between elements at regime of sequential activity that is observed in the ensemble of neuron-like
elements with chemical inhibitory couplings. Method. The research is made with usage of
analytical methods of nonlinear dynamics and computer modeling. Results. The study showed
that the introduction of arbitrarily small electrical coupling into ensemble of Van der Pol oscillators
with chemical synaptic inhibitory couplings leads to the destruction of a stable heteroclinic
contour between saddle limit cycles. We showed also that nonidentity of elements (while
electrical couplings is absent) does not lead to the destruction of heteroclinic contour, what, in
general, is not typical for such systems. Discussion. We suggest to consider studied ensemble
of elements as phenomenological model of neuronal network. Such approach has advantages:
it is possible to study low-dimensional neuronal models and reproduce the main effects that are
observed in more complex models, for example, in biologically realistic model of Hodgkin-
Huxley and in real experiments also.
 

Research target: Computer Science Mathematics
Priority areas: IT and mathematics mathematics
Language: Russian
Full text
DOI
Text on another site
Keywords: neuronsнейроныheteroclinic cycleDuffing–van der Pol oscillatorchemical couplingelectrical couplingхимическая связьэлектрическая связьосциллятор ван дер Полягетероклинический контур
Publication based on the results of:
Topology and chaos in the dynamics of systems, foliations, and deformations of Lie algebras (2018)
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