CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks.
Jiaqi MaBo ChangXuefei ZhangQiaozhu MeiPublished in: CoRR (2020)
Keyphrases
- neural network
- graph theory
- graph representation
- graph matching
- weighted graph
- graph structure
- graph theoretical
- directed graph
- graph mining
- graph databases
- graph construction
- labeled graphs
- graph model
- random graphs
- pattern recognition
- adjacency matrix
- graph classification
- graph structures
- structural pattern recognition
- graph partitioning
- graph theoretic
- graph clustering
- subgraph isomorphism
- graph search
- graph data
- bipartite graph
- series parallel
- graph representations
- spanning tree
- undirected graph
- graph isomorphism
- edge weights
- graph properties
- adjacency graph
- graph transformation
- real world graphs
- evolving graphs
- minimum spanning tree
- maximum clique
- maximum common subgraph
- reachability queries
- dynamic graph
- graph drawing
- disk resident
- average degree
- social graphs
- massive graphs
- structured data
- connected graphs
- graph kernels
- proximity graph
- attributed graphs
- random walk
- artificial neural networks
- strongly connected
- bounded treewidth
- community discovery
- neighborhood graph
- web graph
- back propagation
- hyper graph
- maximum cardinality
- maximum independent set
- connected dominating set
- dense subgraphs
- planar graphs
- maximal cliques
- graph embedding
- fully connected
- small world
- connected components
- social network analysis