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)

Robust Ensemble-Based Evolutionary Calibration of the Numerical Wind Wave Model. - Pavel Vychuzhanin; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (ICCS (1), 2019)

REBEC: Robust Evolutionary-based Calibration Approach for the Numerical Wind Wave Model. - Pavel Vychuzhanin; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (CoRR, 2019)

Automatic evolutionary learning of composite models with knowledge enrichment. - Anna V. Kalyuzhnaya; Nikolay O. Nikitin; Pavel Vychuzhanin; Alexander Hvatov; Alexander Boukhanovsky (GECCO Companion, 2020)

Multi-Objective Evolutionary Design of Composite Data-Driven Models. - Iana S. Polonskaia; Nikolay O. Nikitin; Ilia Revin; Pavel Vychuzhanin; Anna V. Kalyuzhnaya (CEC, 2021)

Automated evolutionary approach for the design of composite machine learning pipelines. - Nikolay O. Nikitin; Pavel Vychuzhanin; Mikhail Sarafanov; Iana S. Polonskaia; Ilia Revin; Irina V. Barabanova; Gleb Maximov; Anna V. Kalyuzhnaya; Alexander Boukhanovsky (Future Gener. Comput. Syst., 2022)

Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea. - Nikolay O. Nikitin; Ilia Revin; Alexander Hvatov; Pavel Vychuzhanin; Anna V. Kalyuzhnaya (Comput. Geosci., 2022)