Масляев Михаил Александрович

Масляев Михаил Александрович
ассистент (квалификационная категория "ассистент"), факультет цифровых трансформаций

Преподаваемые дисциплины в текущем учебном году

  • Автоматическое машинное обучение и моделирование

Педагогический стаж

Общий стаж:
4 года

Публикации

15
Статья
2023 год

Maslyaev M., Hvatov A. Multiobjective evolutionary discovery of equation-based analytical models for dynamical systems. Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics]. 2023. Vol. 23. No. 1(143). pp. 97-104.

Статья
2023 год

Maslyaev M., Hvatov A. Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery. GECCO 2023 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2023. pp. 603–606.

Статья
2023 год

Bykov N., Hvatov A., Andreeva T., Lukin A.Y., Maslyaev M., Obraztsov N.V., Surov A.V., Boukhanovsky A.V. . Methods for a Partial Differential Equation Discovery: Application to Physical and Engineering Problems. Moscow University Physics Bulletin. 2023. Vol. 78. No. Suppl.1. pp. S256-S265.

Статья
2022 год

Maslyaev M., Hvatov A. Solver-Based Fitness Function for the Data-Driven Evolutionary Discovery of Partial Differential Equations. IEEE Congress on Evolutionary Computation, CEC 2022. 2022. pp. 1-8.

Статья
2022 год

Bykov N., Obraztsov N.V., Hvatov A., Maslyaev M., Surov A.V. Hybrid modeling of gas-dynamic processes in AC plasma torches. Физика и механика материалов = Materials Physics and Mechanics. 2022. Vol. 50. No. 2. pp. 287-303.

Статья
2021 год

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
2021 год

Maslyaev M., Hvatov A., Kalyuzhnaya A.V. Partial differential equations discovery with EPDE framework: Application for real and synthetic data (R). Journal of Computational Science. 2021. Vol. 53. pp. 101345.

Статья
2021 год

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.

Статья
2021 год

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.

Статья
2021 год

Maslyaev M., Hvatov A. Multi-Objective Discovery of PDE Systems Using Evolutionary Approach. IEEE Congress on Evolutionary Computation, CEC 2021. 2021. pp. 596-603.

Статья
2020 год

Hvatov A., Maslyaev M. The data-driven physical-based equations discovery using evolutionary approach. GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2020. pp. 129–130.

Статья
2020 год

Maslyaev M., Hvatov A., Kalyuzhnaya A. Data-Driven Partial Differential Equations Discovery Approach for the Noised Multi-dimensional Data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12138 LNCS. pp. 86-100.

Статья
2020 год

Maslyaev M., Hvatov A., Kalyuzhnaya A.V. Discovery of the data-driven models of continuous metocean process in form of nonlinear ordinary differential equations. Procedia Computer Science. 2020. Vol. 178. pp. 18-26.

Статья
2019 год

Maslyaev M., Hvatov A. Discovery of the data-driven differential equation-based models of continuous metocean process. Procedia Computer Science. 2019. Vol. 156. pp. 367-376.

Статья
2019 год

Maslyaev M., Hvatov A., Kalyuzhnaya A.V. Data-driven partial derivative equations discovery with evolutionary approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. Vol. 11540 LNCS. pp. 635-641.

Повышение квалификации

Повышение квалификации
2022 год
Преподаватель в области искусственного интеллекта

Российская Федерация, Санкт-Петербург