| Data-driven modal decomposition methods as feature detection techniques for flow problems: a critical assessment B Begiashvili, N Groun, J Garicano-Mena, S Le Clainche, E Valero Physics of Fluids 35, 2022 | 27 | 2022 |
| pyLOM: A HPC open source reduced order model suite for fluid dynamics applications B Eiximeno, A Miró, B Begiashvili, E Valero, I Rodriguez, O Lehmkuhl arXiv preprint arXiv:2405.15529, 2024 | | 2024 |
| Higher order dynamic mode decomposition beyond aerospace engineering N Groun, B Begiashvili, E Valero, J Garicano-Mena, S Le Clainche Results in Engineering 20, 101471, 2023 | | 2023 |
| Efficient Data-Driven Algorithms to Identify Patterns in Aeronautical Industrial Problems E Lazpita, B Begiashvili, J Garicano, S Le Clainche, E Valero International Symposium on Unmanned Systems and The Defense Industry, 201-206, 2022 | | 2022 |
| Data-Driven Methods Beyond Aerospace Field N Groun, B Begiashvili, E Valero, J Garicano-Mena, S Le Clainche International Symposium on Unmanned Systems and The Defense Industry, 105-110, 2022 | | 2022 |
| A Novel Hybrid Lstm-Cnn1d Architecture for Short-Term Solar Irradiance Forecasting in a Spatio-Temporal Framework B Begiashvili, M Kessler, A Molina-Garcia, MC Bueso-Sanchez Available at SSRN 4490286, 2021 | | 2021 |
| Análisis y control de sistemas estocásticos con aplicaciones en tecnologías cuánticas B Begiashvili | | 2019 |
| CRITICAL EVALUATION OF FEATURE DETECTION ALGORITHMS BASED ON MODAL DECOMPOSITION METHODS B BEGIASHVILI, J GARICANO, S LE CLAINCHE, E VALERO | | |
Eusebio ValeroUniversidad Politecnica de madrid在 upm.es 的电子邮件经过验证
