3 papers
cs.LG2026
Identifying the nonlinear string dynamics with port-Hamiltonian neural networks
Maximino Linares, Guillaume Doras, Thomas Hélie
Hybrid machine learning combines physical knowledge with data-driven models to enhance interpretability and performance. In this context, Port-Hamiltonian Systems (PHS), which gene…
cs.LG2026
Controlled oscillation modeling using port-Hamiltonian neural networks
Maximino Linares, Guillaume Doras, Thomas Hélie
Learning dynamical systems through purely data-driven methods is challenging as they do not learn the underlying conservation laws that enable them to correctly generalize. Existin…
math.DS2023
From equilibrium statistical physics under experimental constraints to macroscopic port-Hamiltonian systems
Judy Najnudel, Thomas Hélie, David Roze +1
This paper proposes to build a bridge between microscopic descriptions of matter with internal energy, composed of many fast interacting particles inside an environment, and their…