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Beatriz Moya García
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Learning slosh dynamics by means of data
B Moya, D González, I Alfaro, F Chinesta, E Cueto
Computational Mechanics 64, 511-523, 2019
352019
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
212022
Physically sound, self-learning digital twins for sloshing fluids
B Moya, I Alfaro, D Gonzalez, F Chinesta, E Cueto
PLoS One 15 (6), e0234569, 2020
212020
Learning physics from data: a thermodynamic interpretation
F Chinesta, E Cueto, M Grmela, B Moya, M Pavelka, M Šípka
Workshop on Joint Structures and Common Foundations of Statistical Physics …, 2020
92020
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
32022
Physics-informed Reinforcement Learning for Perception and Reasoning about Fluids
B Moya, A Badias, D Gonzalez, F Chinesta, E Cueto
arXiv preprint arXiv:2203.05775, 2022
22022
Thermodynamics of the machine learning of physical phenomena
B Moya, D González, F Chinesta, E Cueto
2022
Data Learning of Fluid Dynamics for Physically Informed Digital Twins
B Moya, I Alfaro, D González, F Chinesta, E Cueto
Jornada de Jóvenes Investigadores del I3A 8, 2020
2020
Aprendizaje automatico de dinámica de fluidos mediante modelos de datos
BM Garcia, D González, I Alfaro, F Chinesta, E Cueto
Jornada de Jóvenes Investigadores del I3A 7, 2019
2019
Deep learning of fluid dynamics from free surface data for full state reconstruction and correction
B Moya, A Badıas, Q Hernández, D González, I Alfaro, F Chinesta, ...
Data-driven, reduced-order modelling and simulation of free-surface flows
B Moya, D Gonzalez, I Alfaro, F Chinesta, E Cueto
Manifold learning of complex fluid behavior for real-time simulation
B Moya, D González, I Alfaro, F Chinesta, E Cueto
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Articles 1–12