Learning Physics from Data: A Thermodynamic Interpretation. - Francisco Chinesta; Elías Cueto; Miroslav Grmela; Beatriz Moya; Michal Pavelka; Martin Sípka (SPIGL, 2020)

Physics-informed Reinforcement Learning for Perception and Reasoning about Fluids. - Beatriz Moya; Alberto Badías; David González 002; Francisco Chinesta; Elías Cueto (CoRR, 2022)

Physics Perception in Sloshing Scenes With Guaranteed Thermodynamic Consistency. - Beatriz Moya; Alberto Badías; David González 002; Francisco Chinesta; Elías Cueto (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Thermodynamics-informed super-resolution of scarce temporal dynamics data. - Carlos Bermejo-Barbanoj; Beatriz Moya; Alberto Badías; Francisco Chinesta; Elías Cueto (CoRR, 2024)

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs. - Federico Pichi; Beatriz Moya; Jan S. Hesthaven (J. Comput. Phys., 2024)

Resilience-based post disaster recovery optimization for infrastructure system via deep reinforcement learning. - Huangbin Liang; Beatriz Moya; Francisco Chinesta; Eleni N. Chatzi (Reliab. Eng. Syst. Saf., 2026)