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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Euler Equation: Estimation on Emerging Markets Data

2016.
Khvostova I., Larin A. V., Novak A.
We address the issue of estimating the Euler equation for emerging mar- kets. Using panel data for Russian households, we show that accounting for consumer type and income level is crucial. Consumers, who have nei- ther savings nor loans, as well as consumers with low income, face liquidity constraints so that the Euler equation for them does not hold. The estima- tion for lenders su ers from weak identi cation so that con dence intervals for parameters are wide and any meaningful interpretation is dicult. For consumers with loans, we show that the elasticity of intertemporal sub- stitution (EIS) is signi cantly higher than zero. This result is robust to accounting for possible non-optimal behavior of consumers.
Priority areas: economics
Language: English
Full text
Text on another site
Keywords: развивающиеся рынкиRLMS-HSEмежвременное потреблениеуравнение Эйлера household consumptionEuler equiation emerging marketsмониторинг RLMS-HSE
Publication based on the results of:
Моделирование и эконометрическое тестирование микроэкономических предпосылок в моделях общего равновесия (2015)
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