| 2025 | ICCS | To Select or Not to Select? The Role of Meta-features Selection in Meta-learning Tasks with Tabular Data. | Irina Deeva, Alena Kropacheva |
| 2025 | ICDM | Meta-Features Informed Wgan for Tabular Data. | Roman Netrogolov, Irina Deeva |
| 2024 | GECCO | GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects. | Maiia Pinchuk, Grigorii Kirgizov, Lyubov Yamshchikova, Nikolay O. Nikitin, Irina Deeva, Karine Shakhkyan, Ivan I. Borisov, Kirill Zharkov, Anna V. Kalyuzhnaya |
| 2023 | CEC | A Multi-Contractor Approach for MLRCPSP with the Graph Structure Optimization. | Anastasiia Filatova, Mikhail V. Kovalchuk, Stanislav Batalenkov, Aleksander Voskresenskiy, Irina Deeva, Anna V. Kaluzhnaya, Aleksei Shpilman, Natalia Kondrashova, Maxim Dudnichenko, Denis A. Nasonov |
| 2023 | GECCO | LSevoBN: a structure learning algorithm for large Bayesian networks. | Yury Kaminsky, Irina Deeva |
| 2022 | ICCS | Networks Clustering-Based Approach for Search of Reservoirs-Analogues. | Andrey Bezborodov, Irina Deeva |
| 2021 | ICCS | Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks. | Irina Deeva, Anna Bubnova, Petr D. Andriushchenko, Anton Voskresenskiy, Nikita V. Bukhanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya |
| 2021 | Mobiquitous | A Multimodal Approach to Synthetic Personal Data Generation with Mixed Modelling: Bayesian Networks, GAN's and Classification Models. | Irina Deeva, Andrey Mossyayev, Anna V. Kalyuzhnaya |
| 2019 | GECCO | Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. | Nikolay O. Nikitin, Pavel Vychuzhanin, Alexander Hvatov, Irina Deeva, Anna V. Kalyuzhnaya, Sergey V. Kovalchuk |