| On methods for improving the accuracy of multi-class classification on imbalanced data. LA Sevastyanov, EY Shchetinin ITTMM 20, 70-82, 2020 | 30 | 2020 |
| Cluster-based energy consumption forecasting in smart grids EY Shchetinin Distributed Computer and Communication Networks: 21st International …, 2018 | 30 | 2018 |
| Arrhythmia detection using resampling and deep learning methods on unbalanced data GA Gennadievna Компьютерная оптика 46 (6), 980-987, 2022 | 8 | 2022 |
| Cardiac arrhythmia disorders detection with deep learning models EY Shchetinin, LA Sevastianov, AV Demidova, AG Glushkova International Conference on Distributed Computer and Communication Networks …, 2021 | 6 | 2021 |
| Deep neural networks for emotion recognition EY Shchetinin, LA Sevastianov, DS Kulyabov, EA Ayrjan, AV Demidova International Conference on Distributed Computer and Communication Networks …, 2020 | 6 | 2020 |
| Modeling the energy consumption of smart buildings using artificial intelligence. EY Shchetinin ITTMM (Selected Papers), 130-140, 2019 | 6 | 2019 |
| Extreme copulas modeling with max-stable spatial processes EY Shchetinin Распределенные компьютерные и телекоммуникационные сети: управление …, 2017 | 6 | 2017 |
| On methods of building the trading strategies in the cryptocurrency markets SE Yu Discrete and Continuous Models and Applied Computational Science 30 (1), 79-87, 2022 | 5 | 2022 |
| Study of the impact of the COVID-19 pandemic on international air transportation SE Yu Discrete and Continuous Models and Applied Computational Science 29 (1), 22-35, 2021 | 5 | 2021 |
| Automated detection of COVID-19 coronavirus infection based on analysis of chest X-ray images by deep learning methods EY Shchetinin, LA Sevastyanov | 4 | 2022 |
| Vine copulas structures modeling on Russian stock market SE Yu Discrete and Continuous Models and Applied Computational Science 27 (4), 343-354, 2019 | 4 | 2019 |
| Modeling of extreme precipitation fields on the territoryof the European part of Russia EY Shchetinin, ND Rassakhan Discrete and Continuous Models and Applied Computational Science 26 (1), 74-83, 2018 | 4 | 2018 |
| Improving the energy efficiency of the smart buildings with the boosting algorithms EY Shchetinin, VS Melezhik, LA Sevastyanov Proc. 12th Int. Workshop Applied Problems in Theory of Probabilities and …, 2018 | 4 | 2018 |
| Precipitation Maximum Spatial Dependence Structures Modelling EY Shchetinin, VM Martynova CEUR Workshop Proceedings, 72-77, 2017 | 4 | 2017 |
| On methods of quantitative analysis of the company’s financial indicators under conditions of high risk of investments SE Yu Discrete and Continuous Models and Applied Computational Science 28 (4), 346-360, 2020 | 3 | 2020 |
| Estimation of heavy tail dependence based on copulas for the precipitation analysis LA Sevastianov, ND Rassakhan, EY Shchetinin CEUR Workshop Proceedings 8, 40, 2018 | 3 | 2018 |
| Smart buildings energy savings with gradient boosting algorithm EY Shchetinin, EA Popova Communications in Computer and Information Science, CEUR Workshop …, 2018 | 3 | 2018 |
| Improving the efficiency of energy consumption in smart grids with application of artificial intellect E Shchetinin CEUR Workshop Proc 2267, 313-317, 2018 | 3 | 2018 |
| Anomaly Electrocardiograms Automatic Detection with Unsupervised Deep Learning Methods EY Shchetinin, AG Glushkova, LA Sevastianov International Conference on Distributed Computer and Communication Networks …, 2022 | 2 | 2022 |
| Detection of COVID-19 coronavirus infection in chest X-ray images with deep learning methods EY Shchetinin Computer Optics 46 (6), 963-970, 2022 | 2 | 2022 |