Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves

DOI10.1007/978-3-031-38271-0_57arXiv2302.08232OpenAlexW4385435161MaRDI QIDQ6178891

Sina Ober-Blöbaum, Christian Offen

Publication date: 16 January 2024

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2302.08232

zbMATH Keywords

system identificationtravelling wavesdiscrete Lagrangians

Mathematics Subject Classification ID

Computational learning theory (68Q32) Artificial neural networks and deep learning (68T07) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Smoothness and regularity of solutions to PDEs (35B65) System identification (93B30) Variational methods applied to PDEs (35A15) Error bounds for initial value and initial-boundary value problems involving PDEs (65M15) Numerical methods for inverse problems for initial value and initial-boundary value problems involving PDEs (65M32) Traveling wave solutions (35C07)

Cites Work

• Unnamed Item
• The principle of symmetric criticality
• Variational learning of Euler-Lagrange dynamics from data
• Backward error analysis for variational discretisations of PDEs
• Discrete mechanics and variational integrators
• Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics
• Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds and Approximation with Weakly Symplectic Autoencoder

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