Irina Deeva

According to our database, Irina Deeva authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

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

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

LSevoBN: a structure learning algorithm for large Bayesian networks.

Yury Kaminsky, Irina Deeva

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

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

Proceedings of the IEEE Congress on Evolutionary Computation, 2023

2022

BigBraveBN: algorithm of structural learning for bayesian networks with a large number of nodes.

Yury Kaminsky, Irina Deeva

CoRR, 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

Networks Clustering-Based Approach for Search of Reservoirs-Analogues.

Andrey Bezborodov, Irina Deeva

Proceedings of the Computational Science - ICCS 2022, 2022

2021

MIxBN: library for learning Bayesian networks from mixed data.

Anna V. Bubnova, Irina Deeva, Anna V. Kalyuzhnaya

CoRR, 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

Proceedings of the Mobile and Ubiquitous Systems: Computing, Networking and Services, 2021

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

Proceedings of the Computational Science - ICCS 2021, 2021

2020

Bayesian Networks-based personal data synthesis.

Irina Deeva, Petr D. Andriushchenko, Anna V. Kalyuzhnaya, Alexander V. Boukhanovsky

Proceedings of the GoodTechs '20: 6th EAI International Conference on Smart Objects and Technologies for Social Good, 2020

2019

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

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019