| Forecasting of commercial sales with large scale Gaussian Processes R Rivera, E Burnaev 2017 IEEE International Conference on Data Mining Workshops (ICDMW), 625-634, 2017 | 19 | 2017 |
| Towards forecast techniques for business analysts of large commercial data sets using matrix factorization methods R Rivera, I Nazarov, E Burnaev Journal of Physics: Conference Series 1117 (1), 012010, 2018 | 11 | 2018 |
| Demand forecasting techniques for build-to-order lean manufacturing supply chains R Rivera-Castro, I Nazarov, Y Xiang, A Pletneev, I Maksimov, E Burnaev International Symposium on Neural Networks, 213-222, 2019 | 8 | 2019 |
| Adversarial attacks on deep models for financial transaction records I Fursov, M Morozov, N Kaploukhaya, E Kovtun, R Rivera-Castro, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 6 | 2021 |
| Topological data analysis of time series data for B2B customer relationship management R Rivera-Castro, P Pilyugina, A Pletnev, I Maksimov, W Zhu, E Burnaev 35th IMP-conference in Paris, France, 2019 | 6 | 2019 |
| Topological data analysis for portfolio management of cryptocurrencies R Rivera-Castro, P Pilyugina, E Burnaev 2019 International Conference on Data Mining Workshops (ICDMW), 238-243, 2019 | 5 | 2019 |
| Topology-based clusterwise regression for user segmentation and demand forecasting R Rivera-Castro, A Pletnev, P Pilyugina, G Diaz, I Nazarov, W Zhu, ... 2019 IEEE International Conference on Data Science and Advanced Analytics …, 2019 | 4 | 2019 |
| Cohortney: Deep clustering for heterogeneous event sequences V Zhuzhel, R Rivera-Castro, N Kaploukhaya, L Mironova, A Zaytsev, ... arXiv e-prints, arXiv: 2104.01440, 2021 | 2 | 2021 |
| Topologically-based Variational Autoencoder for Time Series Classification R Rivera-Castro, S Moustafa, P Pilyugina, E Burnaev latinxinai. org, 2020 | 2 | 2020 |
| Graph Neural Networks for Model Recommendation using Time Series Data A Pletnev, R Rivera-Castro, E Burnaev 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 1 | 2020 |
| Addressing cold start in recommender systems with hierarchical graph neural networks I Maksimov, R Rivera-Castro, E Burnaev 2020 IEEE International Conference on Big Data (Big Data), 5128-5137, 2020 | 1 | 2020 |
| DeepFolio: Convolutional neural networks for portfolios with limit order book data A Sangadiev, R Rivera-Castro, K Stepanov, A Poddubny, K Bubenchikov, ... arXiv preprint arXiv:2008.12152, 2020 | 1 | 2020 |
| An industry case of large-scale demand forecasting of hierarchical components R Rivera-Castro, I Nazarov, Y Xiang, I Maksimov, A Pletnev, E Burnaev 2019 18th IEEE International Conference On Machine Learning And Applications …, 2019 | 1 | 2019 |
| Sequence Embeddings Help Detect Insurance Fraud I Fursov, E Kovtun, R Rivera-Castro, A Zaytsev, R Khasyanov, M Spindler, ... IEEE Access 10, 32060-32074, 2022 | | 2022 |
| CAUSALYSIS: Causal Machine Learning for Real-Estate Investment Decisions R Rivera-Castro, E Burnaev 2021 IEEE 8th International Conference on Data Science and Advanced …, 2021 | | 2021 |
| COHORTNEY: Non-Parametric Clustering of Event Sequences V Zhuzhel, R Rivera-Castro, N Kaploukhaya, L Mironova, A Zaytsev, ... arXiv preprint arXiv:2104.01440, 2021 | | 2021 |
| TOTOPO: Classifying univariate and multivariate time series with Topological Data Analysis P Pilyugina, R Rivera-Castro, E Burnaev arXiv preprint arXiv:2010.05056, 2020 | | 2020 |
| Towards forecast techniques for business analysts of large commercial data sets using matrix factorization methods R Rivera-Castro, I Nazarov, E Burnaev arXiv preprint arXiv:2009.04359, 2020 | | 2020 |
| PROCEEDINGS-2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, BIG DATA 2020 I Maksimov, R Rivera-Castro, E Burnaev, ZA Khan, NA Siami | | 2020 |
| E-energy: Trend Report 2009 R Rivera, J Cornelius E-energy, 2009 | | 2009 |
Evgeny BurnaevSkolkovo Institute of Science and TechnologyVerified email at skoltech.ru
