output
20102025
most citedDeep learning of thermodynamics-aware reduced-order models from data

96 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2022★ 18 cited

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

Quercus Hernández, Alberto Badías, Francisco Chinesta +1

We develop inductive biases for the machine learning of complex physical systems based on the port-Hamiltonian formalism. To satisfy by construction the principles of thermodynamic…

cs.LG2020★ 89 cited

Structure-preserving neural networks

Quercus Hernández, Alberto Badias, David Gonzalez +2

We develop a method to learn physical systems from data that employs feedforward neural networks and whose predictions comply with the first and second principles of thermodynamics…