| Neuralprophet: Explainable forecasting at scale O Triebe, H Hewamalage, P Pilyugina, N Laptev, C Bergmeir, ... arXiv preprint arXiv:2111.15397, 2021 | 105 | 2021 |
| 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 | 10 | 2019 |
| Topological data analysis of time series data for B2B customer relationship management R Rivera-Castro, P Pilyugina, A Pletnev, I Maksimov, W Wyz, E Burnaev arXiv preprint arXiv:1906.03956, 2019 | 8 | 2019 |
| Neuralprophet: Explainable forecasting at scale. arXiv 2021 O Triebe, H Hewamalage, P Pilyugina, N Laptev, C Bergmeir, ... arXiv preprint arXiv:2111.15397, 0 | 7 | |
| 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 | 6 | 2019 |
| NeuralProphet: Explainable Forecasting at Scale. 2021 O Triebe, H Hewamalage, P Pilyugina, N Laptev, C Bergmeir, ... URL: https://doi. org/10.48550/arXiv 2111, 2021 | 5 | 2021 |
| 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 | 4 | 2020 |
| Topologically-based Variational Autoencoder for Time Series Classification R Rivera-Castro, S Moustafa, P Pilyugina, E Burnaev latinxinai. org, 2020 | 1 | 2020 |
| Assessing the Risk of Permafrost Degradation with Physics-Informed Machine Learning P Pilyugina, T Chernikov, A Zaytsev, A Bulkin, E Burnaev, I Belalov, ... arXiv preprint arXiv:2310.02525, 2023 | | 2023 |
| 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 |
| Quantum state Tomography A Bozhedarov, A Talitsky, N Shvetsov, P Pilyugina, A Vlasov | | |
