Using Graph Convolutional Networks to Compute Approximations of Dominant Eigenvectors.
Ping-En LuCheng-Shang ChangPublished in: SIGMETRICS Perform. Evaluation Rev. (2020)
Keyphrases
- graph structures
- small world
- graph theory
- graph laplacian
- average degree
- graph structure
- graph model
- laplacian matrix
- fully connected
- graph theoretic
- efficient computation
- graph representation
- random walk
- edge weights
- weighted graph
- social graphs
- clustering coefficient
- deep learning
- spanning tree
- spectral clustering
- directed graph
- complex networks
- network structure
- structured data
- directed edges
- dynamic networks
- structural patterns
- correlation matrix
- degree distribution
- social networks
- network size
- graph construction
- graph clustering
- undirected graph
- bipartite graph
- singular value decomposition
- covariance matrix
- graphical models
- image segmentation