Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds.
Andreas BittracherStefan KlusBoumediene HamziPéter KoltaiChristof SchüttePublished in: J. Nonlinear Sci. (2021)
Keyphrases
- dimensionality reduction
- manifold learning
- low dimensional
- complex systems
- high dimensional data
- high dimensional
- laplacian eigenmaps
- nonlinear dimensionality reduction
- kernel pca
- low dimensional spaces
- feature space
- dimensionality reduction methods
- euclidean space
- high level
- latent space
- input space
- principal component analysis
- management system
- feature extraction
- linear discriminant analysis
- vector space
- distributed systems
- geometric structure
- expert systems
- physical systems
- pattern recognition
- class separability
- real world