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 (GECCO (Companion), 2019)

Bayesian Networks-based personal data synthesis. - Irina Deeva; Petr D. Andriushchenko; Anna V. Kalyuzhnaya; Alexander V. Boukhanovsky (GOODTECHS, 2020)

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 (ICCS (1), 2021)

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 (MobiQuitous, 2021)

MIxBN: library for learning Bayesian networks from mixed data. - Anna V. Bubnova; Irina Deeva; Anna V. Kalyuzhnaya (CoRR, 2021)

Networks Clustering-Based Approach for Search of Reservoirs-Analogues. - Andrey Bezborodov; Irina Deeva (ICCS (1), 2022)

Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering. - Petr D. Andriushchenko; Irina Deeva; Anna Bubnova; Anton Voskresenskiy; Nikita V. Bukhanov; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (CoRR, 2022)

BigBraveBN: algorithm of structural learning for bayesian networks with a large number of nodes. - Yury Kaminsky; Irina Deeva (CoRR, 2022)

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 (CEC, 2023)

LSevoBN: a structure learning algorithm for large Bayesian networks. - Yury Kaminsky; Irina Deeva (GECCO Companion, 2023)

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 (GECCO Companion, 2024)

To Select or Not to Select? The Role of Meta-features Selection in Meta-learning Tasks with Tabular Data. - Irina Deeva; Alena Kropacheva (ICCS (2), 2025)