• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Articles
  • Calibrating for the Future: Enhancing Calorimeter Longevity with Deep Learning
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
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.

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Calibrating for the Future: Enhancing Calorimeter Longevity with Deep Learning

Moscow University Physics Bulletin. 2024. Vol. 79. No. Suppl. 2. P. S591–S597.
Ali S., Ryzhikov A., Derkach D., Ratnikov F., Bocharnikov V.

In the realm of high-energy physics, the longevity of calorimeters is paramount. Our research introduces a deep learning strategy to refine the calibration process of calorimeters used in particle physics experiments. We develop a Wasserstein GAN inspired methodology that adeptly calibrates the misalignment in calorimeter data due to aging or other factors. Leveraging the Wasserstein distance for loss calculation, this innovative approach requires a significantly lower number of events and resources to achieve high precision, minimizing absolute errors effectively. Our work extends the operational lifespan of calorimeters, thereby ensuring the accuracy and reliability of data in the long term, and is particularly beneficial for experiments where data integrity is crucial for scientific discovery.

Research target: Physics Computer Science
Language: English
Full text
DOI
Text on another site
Keywords: машинное обучениекалибровкаcalibrationhigh energy physicsфизика высоких энергийглубокое обучениеMachine learningGenerative Adversarial Neural NetworksDeep learningГенеративные состязательные нейронные сети
Publication based on the results of:
Study of Accurate Fast Simulation Models Using Machine Learning Methods: Solutions Tests (2024)
Similar publications
Non-linear in-band interference cancellation on base of conjugate gradients method
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Comparative Study of Training Methods and Architectures of Echo State Networks
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained) weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
Рефакторинг исходного кода на основе LLM и расширения UML
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Ising models on the hydrogen peroxide and other lattices
Qian X., Deng Y., Shchur L. et al., Physica A: Statistical Mechanics and its Applications 2026 Vol. 696 P. 1–13
We perform a Monte Carlo analysis of the Ising model on many three-dimensional lattices. By means of finite-size scaling we obtain the critical points and determine the scaling dimensions. As expected, the critical exponents agree with the three-dimensional Ising universality class for all models. The irrelevant field, as revealed by the correction-to-scaling amplitudes, appears to ...
Added: May 24, 2026
Coping with AI errors with provable guarantees
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Overcoming the Curse of Dimensionality with Synolitic AI
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Stable On-the-Fly Learning for Dynamic Neural Networks With Delayed Inputs
Kibkalo Vladislav, Chertopolokhov V., Mukhamedov A. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Опыт применения сетевого анализа (SNA) в историческом нарративе полисубъектного региона (на примере валлийской хроники Brut y Tywysogyon)
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Оптические методы детектирования единичных биомолекул: визуализация, сенсорика, секвенирование молекул ДНК
Melentiev P. N., Калмыков А. С., Гритченко А. С. et al., Успехи физических наук 2024 Т. 194 № 11 С. 1130–1145
Представлен краткий обзор достигнутого уровня оптических методов детектирования единичных молекул в биомедицинских приложениях. Показано, что регистрация флуоресценции единичных молекул красителей, ковалентно связанных с антителами (биомолекулами), совместно с использованием современных методов нанофотоники может быть применена для решения различных задач в биологии и медицине: визуализации биомолекул, токсинов, вирусных частиц, определения ультранизких концентраций аналитов напрямую во взятой пробе, ...
Added: May 21, 2026
VACUUM DISCHARGE DRIVEN BY STRIPE LINE STORAGE AS A SOURCE OF EUV RADIATION
Antsiferov P.S., Stepanov L.V., Matiukhin N. D., Review of Scientific Instruments 2025 Vol. 96 No. 12 Article 123506
The article presents the discharge plasma based source of extreme ultraviolet (EUV) radiation. The discharge circuit has been driven by means of stripe line storage with working voltage 10.5 kV. The main feature of the proposed source is that plasma electrons acquire the energy, necessary for the production of multiply charged ions with ionization potentials ...
Added: May 20, 2026
Регистрация спектров на 6.65 метровом ВУФ-УФ спектрометре с помощью многоканального детектора
Анциферов П. С., Степанов Л. В., Матюхин Н. Д., Оптика и спектроскопия 2026 Т. 134 № 2 С. 214–218
Сообщено о разработке системы регистрации спектров на ПЗС-линейке для уникального ВУФ спектрометра, построенного на основе сферической дифракционной решетки с радиусом 6.65 m. Была использована линейка HAMAMATSU S11156-2048-02, которая устанавливалась по касательной к окружности Роуланда с возможностью механического перемещения для сканирования спектра. Были получены спектрограммы в диапазоне длин волн 2130-2270 Angstrem. Описана методика сшивки регистрируемых спектральных ...
Added: May 20, 2026
ML-based Fast Simulation of FARICH Responses
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
On a Possible Method for Separating CO Lines from the Spectrum of the Cosmic Microwave Background
Malinovsky A. M., Пилипенко С. В., Mikhalchenko A. O. et al., Astronomy Reports 2026 Vol. 70 P. 1–6
Radiation from rotational transitions of CO molecules in distant galaxies creates a chaotic background with an intensity reaching 1000 Jy/sr at a wavelength of approximately 1 mm. This background will pose a serious problem, when measuring spectral distortions of the cosmic microwave background, in particular, the mu-distortion, which presumably has an intensity of less than ...
Added: May 19, 2026
Optimizing Computational Infrastructure for Large Language Models in Bioinformatics: A Case Study
Beknazarov N., , in: Parallel Computational Technologies, 19th International Conference, PCT 2025, Moscow, Russia, April 8–10, 2025, Revised Selected Papers. (CCIS, volume 2891)Vol. 2891.: Springer, 2026. P. 3–16.
This paper addresses the challenge of efficiently training Large Language Models (LLMs) on large-scale, sparse omics datasets in high-performance computing (HPC) environments. Using over 1000 BED tracks as a representative data source, we propose a method combining interval-based chunked storage, sparse matrix transformation, and parallel data loading, integrated within a PyTorch Lightning training framework. Our ...
Added: May 19, 2026
Broadband photoluminescence of epitaxial bismuth nanowires and planar nanostructures
Kaveev A. K., Fedorov V. V., Pavlov A. V. et al., Journal of Materials Chemistry C 2026 Vol. 14 No. 7 P. 2697–2705
Bismuth nanostructures represent a promising material platform for semiconductor nanooptoelectronics and colorimetry owing to the multi-colored light reflection and quantum confinement. In this work, we study the photoluminescent properties of bismuth nanostructures grown using molecular beam epitaxy on the planar CaF2/Si(111) surface. We demonstrate the different surface morphologies of Bi, ranging from planar films obtained ...
Added: May 19, 2026
STM study of single phosphorus incorporation into silicon by heating PBr3 on Si(100)
Pavlova T., V.M. Shevlyuga (Шевлюга В. М., Applied Surface Science 2026 Vol. 736 P. 166813–166813
The objective of miniaturizing doped areas in silicon, with the ultimate goal of achieving atomic-precision doping, requires a fundamental understanding of the dopant incorporation process at the atomic level. We present a combined scanning tunneling microscopy (STM) and density functional theory (DFT) investigation of single phosphorus atom incorporation into the Si(100) surface. Phosphorus was supplied ...
Added: May 19, 2026
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
KMHCR: A Key-Controlled Signal-Domain Transformation for 5G IoT Security
Ronglin Z., Wei L., Jiahong C. et al., Journal of Signal Processing Systems 2026 Vol. 98 Article 31
To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key ...
Added: May 16, 2026
От неизвестности к прозрачности: обзор технологий объяснимого ИИ (XAI)
Avdoshin S. M., Pesotskaya E. Y., Информационные технологии 2026 Т. 32 № 4 С. 185–194
With the rapid advancement of artificial intelligence, and deep learning in particular, models have emerged that are capable of delivering highly accurate predictions. However, the internal logic of such models remains difficult to interpret—an issue of critical importance, especially in domains where the correctness of an algorithm directly affects high-stakes decision-making. One promising avenue for ...
Added: May 8, 2026
Точность учебных целей и академическая успешность: панельное исследование на онлайн-курсе
Boitcov M., Adamovich K., Getman A. et al., Психологическая наука и образование 2026 Т. 31 № 2 С. 188–203
Goal setting is widely used in online education and is considered a factor contributing to student motivation and academic performance. However, existing research often overlooks how accurately students formulate their goals and how this accuracy relates to prior learning experience. This study investigates the relationship between goal-setting accuracy and academic performance, as well as the factors ...
Added: May 5, 2026
Современные методы анализа временных рядов в мониторинге и прогнозировании состояния оборудования для механизированной добычи
Neznanov A., Glushko A., Овчинников С. et al., В кн.: Интеллектуальный анализ данных в нефтегазовой отрасли.: М.: ООО «Геомодель Развитие», 2024. С. 140–143.
With the development of monitoring systems, now we have the opportunity to collect key performance indicators of devices in the process of artificial lift. Every day a huge amount of telemetry is generated by our devices, which can be used to forecast the working mode and health state of the equipment after the process of ...
Added: April 29, 2026
Interpretable Machine Learning in Guided Synthesis of Stable Sols Based on Nanosized Titanium Oxides
Glushko A., Neznanov A., Kuz'micheva G. et al., , in: 2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), 5-7 Feb. 2026.: IEEE, 2026. P. 1–6.
This report discusses the guided synthesis of sols containing nanosized titanium(IV) oxides for use in biological and medical applications. These sols vary in size (from ∼2 up to 2000nm) and different stability (from 0 up to 90 days). They are synthesized under changing fabrication conditions (temperature, hydrolysis duration, titanium-containing precursors composition and concentration) without surfactants. ...
Added: April 29, 2026
Machine Learning Approach to Anticancer Activity Prediction of Transition-Metal Complexes Based on a Large-Scale Experimental Database
Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851
In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...
Added: April 23, 2026
LSTM-модель потребления тепловой энергии в многоэтажном жилом здании
Ершов И. А., Системная инженерия и инфокоммуникации 2025 № 4 С. 11–14
The heat consumption of residential buildings is a stochastic series. It is necessary for the design of thermal energy regulators the creation of a neural network model. In the paper, the model is carried out based on Long Short-Term Memory (LSTM). The high accuracy of reproducing the series was achieved by training the model on ...
Added: April 22, 2026
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit