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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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Instrumental Means for the Control and Analysis of Gas Mixtures Based on the Use of Artificial Neural Networks

P. 734–738.
Ivanov A., Kulagin V., Kaperko A., Kuznetsov Y. M., Оболяева Н. М., Chulkova G., Yurin A., Shustrov A.
Editor of translation: S. Shaposhnikov

The article deals with the features of creation of tools for monitoring and neuronet identification of complex gasair mixtures using devices such as 'electronic nose' equipped with semiconductor gas sensitive sensors in the form of matrix are considered. The results of experimental studies on the analysis and recognition of various gas mextures based on the use of artificial neural networks in the proctssing of streaming signals from a gas sensitive matrix.

Language: English
DOI
Keywords: sensorelectronic noseartificial neural networkControl tools

In book

Proceedings of the 2017 International Conference "Quality Management,Transport and Information Security, Information Technologies" (IT&QM&IS)
Proceedings of the 2017 International Conference "Quality Management,Transport and Information Security, Information Technologies" (IT&QM&IS)
St. Petersburg: IEEE, 2017.
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