Christian Offen

CoRR, 2024

Machine learning of continuous and discrete variational ODEs with convergence guarantee and uncertainty quantification.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., April, 2023

Variational learning of Euler-Lagrange dynamics from data.

[BibT_eX]

[DOI]

J. Comput. Appl. Math., 2023

Learning of discrete models of variational PDEs from data.

[BibT_eX]

[DOI]

CoRR, 2023

Learning discrete Lagrangians for variationalPDEs from data and detection of travelling waves.

[BibT_eX]

[DOI]

CoRR, 2023

Hamiltonian Neural Networks with Automatic Symmetry Detection.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Discrete Lagrangians for Variational PDEs from Data and Detection of Travelling Waves.

[BibT_eX]

[DOI]

Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2022

Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery.

[BibT_eX]

[DOI]

CoRR, 2022

Backward error analysis for conjugate symplectic methods.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Variational integration of learned dynamical systems.

[BibT_eX]

[DOI]

CoRR, 2021

Symplectic integration of learned Hamiltonian systems.

[BibT_eX]

[DOI]

CoRR, 2021

Learning ODE Models with Qualitative Structure Using Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Preservation of Bifurcations of Hamiltonian Boundary Value Problems Under Discretisation.

[BibT_eX]

[DOI]

Found. Comput. Math., 2020

Backward error analysis for variational discretisations of partial differential equations.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Symplectic integration of boundary value problems.

[BibT_eX]

[DOI]