Extendable and invertible manifold learning with geometry regularized autoencoders.
Andrés F. DuqueSacha MorinGuy WolfKevin R. MoonPublished in: IEEE BigData (2020)
Keyphrases
- manifold learning
- low dimensional manifolds
- geodesic distance
- semi supervised
- low dimensional
- dimensionality reduction
- nonlinear dimensionality reduction
- high dimensional
- denoising
- diffusion maps
- high dimensional data
- laplacian eigenmaps
- least squares
- dimension reduction
- subspace learning
- underlying manifold
- feature extraction
- head pose estimation
- manifold structure
- neural network
- data sets
- latent space
- locality preserving
- feature space
- manifold learning algorithm
- nonlinear manifold