CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks.
Jiaqi MaBo ChangXuefei ZhangQiaozhu MeiPublished in: ICLR (2021)
Keyphrases
- neural network
- graph representation
- graph theory
- directed graph
- weighted graph
- graph construction
- graph matching
- graph structure
- labeled graphs
- graph structures
- graph databases
- graph model
- graph clustering
- graph mining
- graph theoretic
- graph theoretical
- adjacency matrix
- graph classification
- structural pattern recognition
- pattern recognition
- bipartite graph
- graph search
- graph partitioning
- graph properties
- random graphs
- spanning tree
- graph data
- artificial neural networks
- series parallel
- evolving graphs
- graph patterns
- graph isomorphism
- connected graphs
- graph kernels
- undirected graph
- subgraph isomorphism
- graph transformation
- reachability queries
- graph representations
- graph layout
- bounded treewidth
- adjacency graph
- planar graphs
- dense subgraphs
- directed acyclic
- maximum clique
- minimum spanning tree
- real world graphs
- random walk
- maximum common subgraph
- disk resident
- query graph
- proximity graph
- topological information
- small world
- neighborhood graph
- inexact graph matching
- finding the shortest path
- dynamic graph
- maximum cardinality
- graph drawing
- connected dominating set
- attributed graphs
- structured data
- web graph
- back propagation
- association graph
- maximal cliques
- polynomial time complexity
- edge weights
- frequent subgraphs
- shortest path
- maximum independent set
- connected components
- directed acyclic graph
- graph embedding
- vertex set
- hyper graph
- average degree