Eigenvalues and Spectral Dimension of Random Geometric Graphs in Thermodynamic Regime.
Konstantin AvrachenkovLaura CottatellucciMounia HamidouchePublished in: COMPLEX NETWORKS (1) (2019)
Keyphrases
- laplacian matrix
- spectral decomposition
- spectral methods
- graph theoretical
- covariance matrix
- graph kernels
- eigenvalues and eigenvectors
- adjacency matrix
- reeb graph
- low dimensional
- graph theoretic
- graph matching
- spectral clustering
- graph structure
- graph mining
- graph laplacian
- weighted graph
- undirected graph
- graph partitioning
- geometric information
- experimental data
- singular value decomposition
- heat kernel
- topological information
- high resolution
- graph theory
- remote sensing
- directed graph
- subgraph isomorphism
- principal components
- graph structures
- normalized cut
- bipartite graph
- graph representation