RGB-D Computer Vision Techniques for Simulated Prosthetic Vision. - Jesus Bermudez-Cameo; Alberto Badías-Herbera; Manuel Guerrero-Viu; Gonzalo López-Nicolás; José Jesús Guerrero (IbPRIA, 2017)

Improving the realism of mixed reality through physical simulation. - Alberto Badías; Icíar Alfaro; David González 002; Francisco Chinesta; Elías Cueto (SIGGRAPH Posters, 2018)

Deep learning of thermodynamics-aware reduced-order models from data. - Quercus Hernandez; Alberto Badías; David González 002; Francisco Chinesta; Elías Cueto (CoRR, 2020)

Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning. - Alberto Badías; Ashis Banerjee (CoRR, 2021)

Structure-preserving neural networks. - Quercus Hernandez; Alberto Badías; David González 002; Francisco Chinesta; Elías Cueto (J. Comput. Phys., 2021)

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

Thermodynamics-informed neural networks for physically realistic mixed reality. - Quercus Hernández; Alberto Badías; Francisco Chinesta; Elías Cueto (CoRR, 2022)

Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems. - Quercus Hernández; Alberto Badías; Francisco Chinesta; Elías Cueto (CoRR, 2022)

MORPH-DSLAM: Model Order Reduction for Physics-Based Deformable SLAM. - Alberto Badías; Icíar Alfaro; David González 002; Francisco Chinesta; Elías Cueto (IEEE Trans. Pattern Anal. Mach. Intell., 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)

Thermodynamics-Informed Graph Neural Networks. - Quercus Hernández; Alberto Badías; Francisco Chinesta; Elías Cueto (IEEE Trans. Artif. Intell., 2024)

Neural Network Layer Algebra: A Framework to Measure Capacity and Compression in Deep Learning. - Alberto Badías; Ashis G. Banerjee (IEEE Trans. Neural Networks Learn. Syst., 2024)