Symplectic Gaussian Process Regression of Hamiltonian Flow Maps

11 September 2020

Papers citing "Symplectic Gaussian Process Regression of Hamiltonian Flow Maps"

7 / 7 papers shown

Title
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes Peter Zaspel Michael Günther 39 2 0 26 Jun 2024
Exact Inference for Continuous-Time Gaussian Process Dynamics K. Ensinger Nicholas Tagliapietra Sebastian Ziesche Sebastian Trimpe 29 1 0 05 Sep 2023
Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification Thomas Beckers Tom Z. Jiahao George J. Pappas 31 2 0 15 May 2023
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior Thomas Beckers Jacob H. Seidman P. Perdikaris George J. Pappas PINN 29 17 0 15 May 2023
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems Valentin Duruisseaux T. Duong Melvin Leok Nikolay Atanasov DRL AI4CE 29 12 0 29 Nov 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 40 11 0 11 Oct 2022
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 50 8 0 10 Nov 2021