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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.
June 5, 2026
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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.
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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Sanctions and international interaction improve cooperation to avert climate change

Proceedings of the Royal Society B: Biological Sciences. 2022. Vol. 289. No. 1972. Article 20212174.
Grimalda G., Belianin A. V., Hennig-Schmidt H., Requate T., Ryzhkova M.

Imposing sanctions on non-compliant parties to international agreements is advocated as a remedy for international cooperation failure. Nevertheless, sanctions are costly, and rational choice theory predicts their ineffectiveness in improving cooperation. We test sanctions effectiveness experimentally in international collective-risk social dilemmas simulating efforts to avoid catastrophic climate change. We involve individuals from countries where sanctions were shown to be effective (Germany) or ineffective (Russia) in increasing cooperation. Here, we show that, while this result still holds nationally, international interaction backed by sanctions is beneficial. Cooperation by low cooperator groups increases relative to national cooperation and converges to the levels of high cooperators. This result holds regardless of revealing other group members' nationality, suggesting that participants' specific attitudes or stereotypes over the other country were irrelevant. Groups interacting under sanctions contribute more to catastrophe prevention than what would maximize expected group payoffs. This behaviour signals a strong propensity for protection against collective risks.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: cooperationpunishmentsanctionsclimate changes
Publication based on the results of:
Experimental Study of Expectations and Preferences in Social Interactions (2022)
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