1 code implementation • 9 Apr 2020 • Quercus Hernández, Alberto Badias, David Gonzalez, Francisco Chinesta, Elias Cueto
The method employs a minimum amount of data by enforcing the metriplectic structure of dissipative Hamiltonian systems in the form of the so-called General Equation for the Non-Equilibrium Reversible-Irreversible Coupling, GENERIC [M. Grmela and H. C Oettinger (1997).
1 code implementation • 3 Jul 2020 • Quercus Hernandez, Alberto Badias, David Gonzalez, Francisco Chinesta, Elias Cueto
We present an algorithm to learn the relevant latent variables of a large-scale discretized physical system and predict its time evolution using thermodynamically-consistent deep neural networks.
no code implementations • 1 Sep 2020 • Alberto Badias, Iciar Alfaro, David Gonzalez, Francisco Chinesta, Elias Cueto
We propose a new methodology to estimate the 3D displacement field of deformable objects from video sequences using standard monocular cameras.
no code implementations • 7 Jun 2021 • Abel Sancarlos, Morgan Cameron, Jean-Marc Le Peuvedic, Juliette Groulier, Jean-Louis Duval, Elias Cueto, Francisco Chinesta
The concept of Hybrid Twin (HT) has recently received a growing interest thanks to the availability of powerful machine learning techniques.
no code implementations • 24 Jun 2021 • Beatriz Moya, Alberto Badias, David Gonzalez, Francisco Chinesta, Elias Cueto
Physics perception very often faces the problem that only limited data or partial measurements on the scene are available.
no code implementations • 19 Aug 2021 • Tarek Frahi, Abel Sancarlos, Matthieu Galle, Xavier Beaulieu, Anne Chambard, Antonio Falco, Elias Cueto, Francisco Chinesta
The present paper aims at analyzing the topological content of the complex trajectories that weeder-autonomous robots follow in operation.
1 code implementation • 11 Mar 2022 • Beatriz Moya, Alberto Badias, David Gonzalez, Francisco Chinesta, Elias Cueto
Learning and reasoning about physical phenomena is still a challenge in robotics development, and computational sciences play a capital role in the search for accurate methods able to provide explanations for past events and rigorous forecasts of future situations.
no code implementations • 26 Jul 2022 • Elias Cueto, Francisco Chinesta
Thermodynamics could be seen as an expression of physics at a high epistemic level.