Learning Hamiltonians of constrained mechanical systems

Learning Hamiltonians of constrained mechanical systems

31 January 2022

Papers citing "Learning Hamiltonians of constrained mechanical systems"

12 / 12 papers shown

Title
Symplectic Neural Flows for Modeling and Discovery Priscilla Canizares Davide Murari Carola-Bibiane Schönlieb Ferdia Sherry Zakhar Shumaylov 80 1 0 21 Dec 2024
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics Katharina Friedl Noémie Jaquier Jens Lundell Tamim Asfour Danica Kragic AI4CE 28 0 0 24 Oct 2024
Symplectic Neural Networks Based on Dynamical Systems Benjamin K Tapley 37 1 0 19 Aug 2024
Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators Haakon Noren Sølve Eidnes E. Celledoni 21 3 0 06 Jun 2023
Predictions Based on Pixel Data: Insights from PDEs and Finite Differences E. Celledoni James Jackaman Davide Murari B. Owren 33 1 0 01 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 18 10 0 27 Apr 2023
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity Vincent Souveton Arnaud Guillin J. Jasche G. Lavaux Manon Michel 20 3 0 03 Feb 2023
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 40 10 0 05 Oct 2022
FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities Takashi Matsubara Takaharu Yaguchi PINN 14 7 0 01 Oct 2022
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces Sølve Eidnes Alexander J. Stasik Camilla Sterud Eivind Bøhn S. Riemer-Sørensen 11 17 0 06 Jun 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 19 15 0 28 Feb 2022
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 146 219 0 29 Sep 2019