Search Results for author: Elías Cueto

Found 3 papers, 3 papers with code

Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems

1 code implementation3 Nov 2022 Quercus Hernández, Alberto Badías, Francisco Chinesta, Elías Cueto

We show that the constructed networks are able to learn the physics of complex systems by parts, thus alleviating the burden associated to the experimental characterization and posterior learning process of this kind of systems.

Thermodynamics-informed neural networks for physically realistic mixed reality

1 code implementation24 Oct 2022 Quercus Hernández, Alberto Badías, Francisco Chinesta, Elías Cueto

The imminent impact of immersive technologies in society urges for active research in real-time and interactive physics simulation for virtual worlds to be realistic.

Mixed Reality

Thermodynamics-informed graph neural networks

1 code implementation3 Mar 2022 Quercus Hernández, Alberto Badías, Francisco Chinesta, Elías Cueto

In this paper we present a deep learning method to predict the temporal evolution of dissipative dynamic systems.

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