Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs.
Qimai LiXiaotong ZhangHan LiuQuanyu DaiXiao-Ming WuPublished in: KDD (2021)
Keyphrases
- graph representation
- graph construction
- graph structure
- graph theory
- graph matching
- weighted graph
- unsupervised and semi supervised learning
- directed graph
- graph databases
- graph theoretic
- graph classification
- graph mining
- semi supervised
- series parallel
- labeled graphs
- graph theoretical
- graph model
- adjacency matrix
- graph structures
- graph partitioning
- subgraph isomorphism
- graph data
- graph properties
- undirected graph
- graph clustering
- random graphs
- graph search
- structural pattern recognition
- bipartite graph
- graph representations
- graph isomorphism
- dynamic graph
- spanning tree
- maximum common subgraph
- reachability queries
- massive graphs
- graph kernels
- edge weights
- structured data
- topological information
- maximum clique
- dense subgraphs
- attributed graphs
- community discovery
- minimum spanning tree
- finding the shortest path
- web graph
- connected graphs
- random walk
- graph layout
- graph patterns
- planar graphs
- maximal cliques
- machine learning
- connected components
- semi supervised learning
- pairwise
- small world