Low-dimensional statistical manifold embedding of directed graphs.
Thorben FunkeTian GuoAlen LancicNino Antulov-FantulinPublished in: ICLR (2020)
Keyphrases
- directed graph
- low dimensional
- manifold embedding
- manifold learning
- high dimensional
- dimension reduction
- random walk
- head pose estimation
- high dimensional data
- dimensionality reduction
- manifold structure
- principal component analysis
- euclidean space
- input space
- subspace learning
- vector space
- data points
- embedding space
- feature space
- multidimensional scaling
- nonlinear dimensionality reduction
- low dimensional manifolds
- computer vision
- high dimensionality
- graph structure
- latent space