Никитин Николай Олегович

Статья

Borisova J., Nikitin N. Lightweight Neural Ensemble Approach for Arctic Sea Ice Forecasting. IEEE Congress on Evolutionary Computation, CEC 2024. 2024. pp. 1-8.

Статья

Getmanov A., Nikitin N.O. Evolutionary Automated Machine Learning for Light-Weight Multi-Modal Pipelines. IEEE Congress on Evolutionary Computation, CEC 2024. 2024. pp. 1-8.

Тезисы

Generative AI for Co-Crystal Design with Property Control

Статья

Иов И.Л., Никитин Н.О. Feature Engineering Pipeline Optimization in AutoML Workflow Using Large Language Models. Proceedings of Artificial Intelligence and Natural Language AINL. 2024. pp. 0.

Статья

Kirgizov G., Nikitin N.O., Pinchuk M., Yamshchikova L., Deeva I., Shakhkyan K., Borisov I.I., Zharkov K.D., Kalyuzhnaya A.V. Automated Design of Graph-based Models and Structures using Modular Evolutionary Framework. 4th workshop on Graphs and more Complex structures for Learning and Reasoning (GCLR 2024). Colocated with AAAI 2024. 2024. pp. accepted-papers.

Статья

Pinchuk M., Kirgizov G., Yamshchikova L., Nikitin N., Deeva I., Shakhkyan K., Borisov I., Zharkov K., Kalyuzhnaya A. GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects. GECCO 2024 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2024. pp. 1668-1675.

Статья

Starodubcev N., Nikitin N., Andronova E., Gavaza K., Sidorenko D., Kalyuzhnaya A.V. Generative design of physical objects using modular framework. Engineering Applications of Artificial Intelligence. 2023. Vol. 119. pp. 105715.

Статья

Klimova A., Nasonov D., Hvatov A., Nikitin N.O., Ivanov S.V., Kalyuzhnaya A.V., Boukhanovsky A. Strategic Trends in Artificial Intelligence Through Impact of Computational Science: What Young Scientists Should Expect. Procedia Computer Science. 2023. Vol. 229. pp. 1-7.

Статья

Stebenkov A.S., Nikitin N.O. Automated Generation of Ensemble Pipelines using Policy-Based Reinforcement Learning method. Procedia Computer Science. 2023. Vol. 229. pp. 70-79.

Статья

Nikitin N.O., Pinchuk M., Pokrovskii V., Shevchenko P., Getmanov A., Aksenkin Y., Revin I., Stebenkov A., Latypov V., Poslavskaya E., Kalyuzhnaya A.V. Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines. Knowledge-Based Systems. 2023. Vol. 302. pp. 112363.

Статья

Nikitin N.O., Teryoshkin S., Pokrovskii V., Pakulin S., Nasonov D. Improvement of Computational Performance of Evolutionary AutoML in a Heterogeneous Environment. IEEE Congress on Evolutionary Computation, CEC 2023. 2023. pp. 1-8.

Учебник, учебное пособие

Современные методы оптимизации с примерами на Python

Статья

Revin I., Potemkin V., Balabanov N., Nikitin N.O. Automated machine learning approach for time series classification pipelines using evolutionary optimization. Knowledge-Based Systems. 2023. Vol. 268. pp. 110483.

Статья

Starodubcev N., Nikitin N.O., Kalyuzhnaya A.V. Surrogate-Assisted Evolutionary Generative Design Of Breakwaters Using Deep Convolutional Networks. IEEE Congress on Evolutionary Computation, CEC 2022. 2022. pp. 1-8.

Статья

Sarafanov M., Pokrovskii V., Nikitin N.O. Evolutionary Automated Machine Learning for Multi-Scale Decomposition and Forecasting of Sensor Time Series. IEEE Congress on Evolutionary Computation, CEC 2022. 2022. pp. 1-8.

Статья

Nikitin N.O., Revin I., Hvatov A., Vychuzhanin P., Kalyuzhnaya A.V. Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea. Computers and Geosciences. 2022. Vol. 161. pp. 105061.

Статья

Sarafanov M., Nikitin N.O., Kalyuzhnaya A.V. Automated Data-Driven Approach for Gap Filling in the Time Series Using Evolutionary Learning. Advances in Intelligent Systems and Computing. 2022. Vol. 1401. pp. 633-642.

Статья

Nikitin N.O., Vychuzhanin P., Sarafanov M., Polonskaia I.S., Revin I., Barabanova I.V., Kaluzhnaya A.V., Boukhanovsky A. Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines. Future Generation Computer Systems. 2022. Vol. 127. pp. 109-125.

Тезисы

Применение методов автоматического машинного обучения для прогнозирования временных рядов

Статья

Borisova J., Aladina A., Nikitin N.O. Hybrid Modelling of Environmental Processes using Composite Models. Procedia Computer Science. 2021. Vol. 193. pp. 256-265.

Статья

Barabanova I.V., Vychuzhanin P., Nikitin N.O. Sensitivity Analysis of the Composite Data-Driven Pipelines in the Automated Machine Learning. Procedia Computer Science. 2021. Vol. 193. pp. 484-493.

Статья

Polonskaia I.S., Aliev I.R., Nikitin N.O. Automated Evolutionary Design of CNN Classifiers for Object Recognition on Satellite Images. Procedia Computer Science. 2021. Vol. 193. pp. 210-219.

Статья

Nikitin N.O., Vychuzhanin P., Sarafanov M., Polonskaia I.S., Kaluzhnaya A.V. Multi-Purpose Evolutionary AutoML for the Generative Design of Composite Modelling Pipelines. KDD-AutoML Workshop 2021. 2021. pp. 1-6.

Статья

Nikitin N.O., Hvatov A., Polonskaia I.S., Kalyuzhnaya A.V., Grigorev G., Wang X., Qian X. Generative design of microfluidic channel geometry using evolutionary approach. GECCO 2021 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2021. pp. 59-60.

Статья

Sarafanov M.I., Borisova Y., Maslyaev M., Revin I., Maximov G., Nikitin N.O. Short-Term River Flood Forecasting Using Composite Models and Automated Machine Learning: The Case Study of Lena River. Water. 2021. Vol. 13. No. 24. pp. 3482.

Статья

Polonskaia I.S., Nikitin N.O., Revin I., Vychuzhanin P., Kaluzhnaya A.V. Multi-Objective Evolutionary Design of Composite Data-Driven Models. IEEE Congress on Evolutionary Computation, CEC 2021. 2021. pp. 926-933.

Статья

Deeva I., Bubnova A., Andriushchenko P.D., Voskresenskiy A., Bukhanov N.V., Nikitin N.O., Kalyuzhnaya A.V. Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2021. Vol. 12742. pp. 394-407.

Статья

Hvatov A., Maslyaev M., Polonskaia I.S., Sarafanov M.I., Merezhnikov M., Nikitin N.O. Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models. Communications in Computer and Information Science. 2021. Vol. 1488. pp. 72-85.

Тезисы

Интерактивный анализ и визуализация процессов идентификации композитных моделей

Статья

Nikitin N.O., Polonskaia I.S., Kalyuzhnaya A.V., Boukhanovsky A.V. The multi-objective optimisation of breakwaters using evolutionary approach. Proceedings of the 5th International Conference on Maritime Technology and Engineering, MARTECH 2020. 2021. Vol. 2. pp. 767-774.

Тезисы

Оценка чувствительности композитных моделей в рамках фреймворка автоматического машинного обучения

Тезисы

Платформа интерактивного построения композитных моделей на основе автоматического машинного обучения

Статья

Kalyuzhnaya A.V., Nikitin N.O., Hvatov A., Maslyaev M., Yachmenkov M., Boukhanovsky A.V. Towards generative design of computationally efficient mathematical models with evolutionary learning. Entropy. 2021. Vol. 23. No. 1. pp. 28.

Тезисы

Применение методов машинного обучения для заполнения пропусков в данных дистанционного зондирования

Статья

Никитин Н.О., Полонская Я.С., Калюжная А.В. Интеллектуальное проектирование защитных сооружений на шельфе с применением моделей морской среды и методов оптимизации. Комплексные исследования Мирового океана: материалы V Всероссийской научной конференции молодых ученых (Калининград, 18-22мая 2020г.). 2020. С. 141-142.

Статья

Kaluzhnaya A.V., Nikitin N.O., Vychuzhanin P., Hvatov A., Boukhanovsky A.V. Automatic Evolutionary Learning of Composite Models With Knowledge Enrichment. GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2020. pp. 43-44.

Статья

Sarafanov M., Kazakov E.E., Nikitin N.O., Kalyuzhnaya A.V. A Machine Learning Approach for Remote Sensing Data Gap-Filling with Open-Source Implementation: An Example Regarding Land Surface Temperature, Surface Albedo and NDVI. Remote Sensing. 2020. Vol. 12. No. 23. pp. 3865.

Статья

Калюжная А.В., Никитин Н.О., Вычужанин П.В., Хватов А.А. Технологии прикладного искусcтвенного интеллекта в задачах численного моделирования процессов в океане. Комплексные исследования Мирового океана: материалы V Всероссийской научной конференции молодых ученых (Калининград, 18-22мая 2020г.). 2020. С. 81-82.

Статья

Nikitin N.O., Polonskaia I.S., Vychuzhanin P., Barabanova I.V., Kaluzhnaya A.V. Structural Evolutionary Learning for Composite Classification Models. Procedia Computer Science. 2020. Vol. 178. pp. 414-423.

Статья

Deeva I., Nikitin N.O., Kalyuzhnaya A.V. Pattern Recognition in Non-Stationary Environmental Time Series Using Sparse Regression. Procedia Computer Science. 2019. Vol. 156. pp. 357-366.

Статья

Nikitin N.O., Deeva I., Vychuzhanin P., Kalyuzhnaya A.V., Hvatov A., Kovalchuk S.V. Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. 2019. pp. 1583-1591.

Статья

Vychuzhanin P., Nikitin N.O., Kalyuzhnaya A.V. Robust Ensemble-Based Evolutionary Calibration of the Numerical Wind Wave Model. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. Vol. 11536. pp. 614-627.

Статья

Khvatov A.A., Nikitin N., Kaluzhnaya A.V., Kosukhin S.S. Adaptation of NEMO-LIM3 model for multigrid high-resolution Arctic simulation. Ocean Modelling. 2019. Vol. 141. pp. 101427.

Тезисы

Эволюционный подход к управлению качеством ансамблевых моделей

Статья

Nikitin N.O., Kalyuzhnaya A.V., Bochenina K., Kudryashov A., Uteuov A., Derevitskii I., Boukhanovsky A.V. Evolutionary ensemble approach for behavioral credit scoring. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018. Vol. 10862. pp. 825-831.

Статья

Kovalchuk S.V., Kisliakovskii I.O., Metsker O.G., Nikitin N.O., Funkner A.A., Kalyuzhnaya A.V., Vaganov D.A., Bochenina K.O. Towards management of complex modeling through a hybrid evolutionary identification. GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion. 2018. pp. 255-256.

Статья

Kalyuzhnaya A.V., Nikitin N.O., Butakov N.A., Nasonov D.A. Precedent-based approach for the identification of deviant behavior in social media. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018. Vol. 10862. pp. 846-852.

Статья

Araya-Lopez J., Nikitin N.O., Kalyuzhnaya A.V. Case-adaptive ensemble technique for met-ocean data restoration. Procedia Computer Science. 2018. Vol. 136. pp. 311-320.

Статья

Kovalchuk S.V. ., Metsker O.G., Funkner A.A., Kisliakovskii I.O., Nikitin N.O., Kalyuzhnaya A.V., Vaganov D.A., Bochenina K.O. A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification. Complexity. 2018. pp. 5870987.

Статья

Noymanee J., Nikitin N.O., Kaluzhnaya A.V. Urban Pluvial Flood Forecasting using Open Data with Machine Learning Techniques in Pattani Basin. Procedia Computer Science. 2017. Vol. 119. pp. 288-297.

Статья

Никитин Н.О. Программный комплекс для моделирования синтетических циклонов. Свидетельство о регистрации программы для ЭВМ. 2017. Т. 2017616937. № от 20.06.2017.

Статья

Nikitin N.O., Spirin D.S., Visheratin A.A., Kalyuzhnaya A.V. Statistics-based models of flood-causing cyclones for the Baltic Sea region. Procedia Computer Science. 2016. Vol. 101. pp. 272–281.

Тезисы

Использование индексирования для аннотирования документов