Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes.
Paul SchwerdtnerPhilipp SchulzeJules BermanBenjamin PeherstorferPublished in: CoRR (2023)
Keyphrases
- recurrent neural network model
- neural model
- differential equations
- neural network
- network architecture
- partial differential equations
- vector space
- nonlinear model predictive control
- manifold learning
- low dimensional
- dimensionality reduction
- diffusion equation
- nonlinear dynamics
- data sets
- bio inspired
- feature selection
- ordinary differential equations
- image based visual servoing