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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
‘In the Age of Technology, It Is Interesting to Look into the Past and Think about What We Can Take from It
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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Annals of DAAAM and Proceedings of the International DAAAM Symposium

Vol. 31(1): Proceedings of the 31st International DAAAM Virtual Symposium ''Intelligent Manufacturing & Automation''. Wien : DAAAM International Vienna, 2020.
Under the general editorship: B. Katalinic

The 31st DAAAM International Symposium on Intelligent Manufacturing and Automation was organised as virtual online conference hosted by the University of Mostar, Mostar, Bosnia and Herzegovina, between the 21st and 24th October 2020, during the DAAAM International Week. The Symposium was organized by DAAAM International Vienna in cooperation with ÖIAV 1848, Vienna University of Technology, International Academy of Engineering, University of Mostar and University of Applied Sciences – Technikum Wien and Under the Auspices of the Danube Rectors’ Conference & Rectors’ and Presidents’ Honor Committee of DAAAM International for 2020. This year’s symposium aimed at continuing the success of the previous years, focusing on the five-fold traditional objectives of the symposium: the presentation of the most recent high-quality results, support of development of young scientists and researchers, organization of international (summer) doctoral school, inauguration of new members of Central European Branch of International Academy of Engineering and the provision of the necessary setting for stimulating discussions, brainstorming and networking among European and international researchers coming both from the academia government agencies and industry.

The papers discuss many aspects of modern manufacturing and automation such as: Algorithms, Artificial Intelligence, CAX, Computer Integration, Control, Cutting Tools, Design, FEM, Invited Lectures, Knowledge, Management, Manufacturing System, Mechatronics, Methodology, Methods, Modelling, Optimization, Robotics, Simulation, Technical Solutions, Technology and Trends.

Chapters
BIG DATA-DRIVEN DIGITAL ECOSYSTEM FRAMEWORK FOR RAILWAY REPORTING
Suleykin, A., Panfilov, P., , in: Annals of DAAAM and Proceedings of the International DAAAM SymposiumVol. 31(1): Proceedings of the 31st International DAAAM Virtual Symposium ''Intelligent Manufacturing & Automation''.: Wien: DAAAM International Vienna, 2020. Ch. 70 P. 0499–0509.
In our application research, we propose a Digital Ecosystem approach to overcome data integration, orchestration and quality challenges in railway reporting system using Big Data technologies. We are building a Digital Ecosystem Framework consisting of different Agents, where each Agent is an essential part of the Railway Reporting Management System. In this work, we address ...
Added: October 27, 2020
Research target: Computer Science Social Sciences Engineering and Technology
Priority areas: economics law IT and mathematics business informatics mathematics engineering science
Language: English
Text on another site
Keywords: automationsimulation modelingcomputer aided design Intelligent Manufacturingrobotics and mechatronicstechnology and trendscomputer aided manufacturingdigital transformation
Annals of DAAAM and Proceedings of the International DAAAM Symposium
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Почему растущие доходы не делают людей счастливее: эмоциональное объяснение парадокса Истерлина (Why Growing Incomes Do Not Make People Happier: an Emotional Explanation of the Easterlin Paradox)
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Generalizing the Brady-Yong Algorithm: Efficient Fast Hough Transform for Arbitrary Image Sizes
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Universal Comparison Methodology for Hough Transform Approaches
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