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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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Routing Algorithms in Optimal Degree Four Circulant Networks Based on Relative Addressing: Comparative Analysis for Networks-on-Chip

IEEE Transactions on Network Science and Engineering. 2023. Vol. 10. No. 1. P. 413–425.
Monakhova E. A., Monakhov O. G., Romanov A.

The solution of the problem of organizing optimal communications in circulant networks of degree four is considered. For a family of optimal circulant networks with the minimum diameter and average distance for any number of nodes in a graph, we propose an optimal pair routing algorithm of constant complexity based on using the relative addressing of nodes in a network. The new algorithm is an analytical extension to any number of nodes in the network of the routing method proposed for dense Gaussian networks, and it does not use division operations, which are very expensive to implement in fixed-point format. This extension is based on the proposed scheme of transformations on the plane of geometrical patterns of optimal circulant networks. The developed routing algorithm is the basis for generating the series of routing algorithms for different subfamilies of the optimal two-dimensional circulants. The general routing algorithm and its modification for a separate subclass of circulants are implemented in the HDL NoC model with circulant topology. All the algorithm parameters important for networks-on-chip, including the consumption of memory, logical resources, and execution time are comprehensively investigated. The results of a comparative analysis of the new algorithms with other routing algorithms, previously implemented in the networks-on-chip, are presented.

Research target: Electronics and Electrical Engineering Computer Science
Language: English
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Keywords: routingnetwork-on-chipcirculant topology
Publication based on the results of:
Automation of networks-on-chip modeling (2023)
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