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News
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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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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?

Some Problems of the Simulation Model Efficiency and Flexibility

P. 532–538.
Mikov A., Kozlov A., Zamyatina E., Ermakov S.
Simulation remains one of the most popular and sometimes the only method of investigation of the complex dynamical systems nowadays. The problems become more and more complicate and so simulation models become complicate and large scale too. So the modelers have to reduce the time of simulation run and overall time of the simulation model design, it’s verification, validation and simulation experiment. The authors believe that the problem of efficiency and flexibility of simulation systems (program tools and linguistic construction) can be solved through it’s automation and intellectualization. This paper discusses the problem of design and implementa-tion of the distributed and parallel simulation systems using the power of several compute nodes of computer network (or cluster or multiprocessor computer). Authors suggest original approach to the synchronization and load balancing of the objects of distributed simulation model. Furthermore authors consider the problem of reduction of time needed to design and to debug a simulation model, the problems of the simulation tools adaptability and offer using models and methods of artificial intelligence in these cases
Language: English
Full text
Keywords: ontologymulti-agent systemsparallel and distributed simulationoptimistic and conservative algorithmsautomatic simulation model completenessload balancing

In book

Proceedings of 8th EUROSIM Congress on Modelling and Simulation "EUROSIM 2013», Сarrdiff, Wales, United Kingdom, 10-13 of September, ISBN 978-0-7695-5073-2
Cardiff: IEEE Computer Society, 2013.
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