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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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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.
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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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Search for CP violation in Ξ+c→pK−π+ decays using model-independent techniques

The European Physical Journal C - Particles and Fields. 2020. Vol. 80. Article 986.
Aaij R., Arzymatov K., Baranov A., Belavin V., Borisyak M., Ratnikov F., Ustyuzhanin A., Boldyrev A., Derkach D., Ryzhikov A., Hushchyn M., Kazeev N., Maevskiy A.

A first search for CPCP violation in the Cabibbo-suppressed Ξ+c→pK−π+Ξc+→pK−π+ decay is performed using both a binned and an unbinned model-independent technique in the Dalitz plot. The studies are based on a sample of proton-proton collision data, corresponding to an integrated luminosity of 3.0fb−13.0fb−1, and collected by the LHCb experiment at centre-of-mass energies of 7 and 8TeV8TeV. The data are consistent with the hypothesis of no CPCP violation.

Research target: Computer Science Physics
Priority areas: IT and mathematics engineering science
Language: English
DOI
Text on another site
Keywords: Experimental High Energy Physics and Elementary Particles PhysicsФизика высоких энергий
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