| Deep learning of thermodynamics-aware reduced-order models from data Q Hernandez, A Badias, D Gonzalez, F Chinesta, E Cueto Computer Methods in Applied Mechanics and Engineering 379, 113763, 2021 | 95 | 2021 |
| Structure-preserving neural networks Q Hernández, A Badías, D González, F Chinesta, E Cueto Journal of Computational Physics 426, 109950, 2021 | 92 | 2021 |
| Thermodynamics-informed graph neural networks Q Hernández, A Badías, F Chinesta, E Cueto IEEE Transactions on Artificial Intelligence 5 (3), 967-976, 2022 | 63 | 2022 |
| Digital twins that learn and correct themselves B Moya, A Badías, I Alfaro, F Chinesta, E Cueto International Journal for Numerical Methods in Engineering 123 (13), 3034-3044, 2022 | 59 | 2022 |
| Model order reduction for real-time data assimilation through extended Kalman filters D González, A Badias, I Alfaro, F Chinesta, E Cueto Computer Methods in Applied Mechanics and Engineering 326, 679-693, 2017 | 45 | 2017 |
| Reduced order modeling for physically-based augmented reality A Badías, I Alfaro, D González, F Chinesta, E Cueto Computer Methods in Applied Mechanics and Engineering 341, 53-70, 2018 | 38 | 2018 |
| An augmented reality platform for interactive aerodynamic design and analysis A Badías, S Curtit, D González, I Alfaro, F Chinesta, E Cueto International Journal for Numerical Methods in Engineering 120 (1), 125-138, 2019 | 34 | 2019 |
| Local proper generalized decomposition A Badías, D González, I Alfaro, F Chinesta, E Cueto International Journal for Numerical Methods in Engineering 112 (12), 1715-1732, 2017 | 31 | 2017 |
| Thermodynamics-informed neural networks for physically realistic mixed reality Q Hernández, A Badías, F Chinesta, E Cueto Computer Methods in Applied Mechanics and Engineering 407, 115912, 2023 | 21 | 2023 |
| Real‐time interaction of virtual and physical objects in mixed reality applications A Badías, D González, I Alfaro, F Chinesta, E Cueto International Journal for Numerical Methods in Engineering 121 (17), 3849-3868, 2020 | 19 | 2020 |
| Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Q Hernández, A Badías, F Chinesta, E Cueto Computational Mechanics 72 (3), 553-561, 2023 | 17 | 2023 |
| Physics perception in sloshing scenes with guaranteed thermodynamic consistency B Moya, A Badias, D Gonzalez, F Chinesta, E Cueto IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 2136-2150, 2022 | 17 | 2022 |
| Morph-dslam: Model order reduction for physics-based deformable slam A Badias, I Alfaro, D Gonzalez, F Chinesta, E Cueto IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 7764 …, 2021 | 12 | 2021 |
| A thermodynamics-informed active learning approach to perception and reasoning about fluids B Moya, A Badías, D González, F Chinesta, E Cueto Computational Mechanics 72 (3), 577-591, 2023 | 11 | 2023 |
| Empowering advanced driver-assistance systems from topological data analysis T Frahi, F Chinesta, A Falcó, A Badias, E Cueto, HY Choi, M Han, ... Mathematics 9 (6), 634, 2021 | 10 | 2021 |
| RGB-D computer vision techniques for simulated prosthetic vision J Bermudez-Cameo, A Badias-Herbera, M Guerrero-Viu, G Lopez-Nicolas, ... Pattern Recognition and Image Analysis: 8th Iberian Conference, IbPRIA 2017 …, 2017 | 9 | 2017 |
| Physics-informed reinforcement learning for perception and reasoning about fluids B Moya, A Badias, D Gonzalez, F Chinesta, E Cueto arXiv e-prints, arXiv: 2203.05775, 2022 | 4 | 2022 |
| Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling B Moya, A Badías, D González, F Chinesta, E Cueto Archives of Computational Methods in Engineering 31 (4), 1897-1914, 2024 | 3 | 2024 |
| Neural network layer algebra: A framework to measure capacity and compression in deep learning A Badias, AG Banerjee IEEE Transactions on Neural Networks and Learning Systems, 2023 | 3 | 2023 |
| Thermodynamics-informed super-resolution of scarce temporal dynamics data C Bermejo-Barbanoj, B Moya, A Badías, F Chinesta, E Cueto arXiv preprint arXiv:2402.17506, 2024 | 1 | 2024 |
Elias CuetoProfessor, Aragon Inst. of Engng. Research. Universidad de Zaragoza.Email verificata su unizar.es