Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds

24 May 2023

Papers citing "Symplectic model reduction of Hamiltonian systems using data-driven quadratic manifolds"

7 / 7 papers shown

Title
Nonlinear energy-preserving model reduction with lifting transformations that quadratize the energy Harsh Sharma Juan Diego Draxl Giannoni Boris Kramer 43 0 0 04 Mar 2025
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
Data-driven identification of latent port-Hamiltonian systems J. Rettberg Jonas Kneifl Julius Herb Patrick Buchfink Jörg Fehr B. Haasdonk PINN 26 2 0 15 Aug 2024
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling Nicholas Galioto Harsh Sharma Boris Kramer Alex Arkady Gorodetsky 38 0 0 23 Jan 2024
Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes Paul Schwerdtner Philipp Schulze Jules Berman Benjamin Peherstorfer 21 6 0 11 Oct 2023
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics P. Goyal Süleyman Yıldız P. Benner 36 2 0 26 Aug 2023
Data-Driven Identification of Quadratic Representations for Nonlinear Hamiltonian Systems using Weakly Symplectic Liftings Süleyman Yıldız P. Goyal Thomas Bendokat P. Benner 14 10 0 02 Aug 2023