Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era.
Eleni D. KoronakiNikolaos EvangelouCristina P. Martin-LinaresEdriss S. TitiIoannis G. KevrekidisPublished in: J. Comput. Phys. (2024)
Keyphrases
- nonlinear dimensionality reduction
- manifold learning
- dimensionality reduction
- low dimensional
- maximum likelihood
- high dimensional data
- laplacian eigenmaps
- partial differential equations
- maximum variance unfolding
- level set
- riemannian manifolds
- high dimensional
- image processing
- dimensionality reduction methods
- locally linear embedding
- multiscale
- machine learning
- semi supervised
- euclidean space
- data visualization