Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge
with Data-Driven Control

Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control

9 January 2023

Ufuk Topcu

Papers citing "Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control"

6 / 6 papers shown

Title
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control T. Duong Abdullah Altawaitan Jason Stanley Nikolay A. Atanasov 23 9 0 17 Jan 2024
Refining Human-Centered Autonomy Using Side Information Adam J. Thorpe 21 0 0 09 May 2023
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 34 68 0 14 Sep 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty 52 34 0 12 Feb 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 121 422 0 10 Mar 2020
Conditional mean embeddings as regressors - supplementary Steffen Grunewalder Guy Lever Luca Baldassarre Sam Patterson A. Gretton Massimiliano Pontil 80 143 0 21 May 2012