We show how to learn discrete field theories from observational data of
...
The article shows how to learn models of dynamical systems from data whi...
Recently, Hamiltonian neural networks (HNN) have been introduced to
inco...
When learning continuous dynamical systems with Gaussian Processes, comp...
By one of the most fundamental principles in physics, a dynamical system...
Hamilton-Jacobi reachability methods for safety-critical control have be...
The principle of least action is one of the most fundamental physical
pr...
Hamiltonian systems are differential equations which describe systems in...
We study the order of convergence of Galerkin variational integrators fo...
Many problems in science and engineering require the efficient numerical...
Recent advances in learning techniques have enabled the modelling of
dyn...