Generalizing Graph Neural Networks on Out-Of-Distribution Graphs.
Shaohua FanXiao WangChuan ShiPeng CuiBai WangPublished in: CoRR (2021)
Keyphrases
- neural network
- graph representation
- graph theory
- graph databases
- weighted graph
- graph structure
- directed graph
- adjacency matrix
- graph matching
- graph construction
- graph theoretic
- graph classification
- labeled graphs
- pattern recognition
- graph mining
- graph model
- structural pattern recognition
- graph structures
- graph search
- graph properties
- degree distribution
- series parallel
- graph clustering
- dynamic graph
- graph partitioning
- subgraph isomorphism
- undirected graph
- back propagation
- random graphs
- bipartite graph
- graph kernels
- graph isomorphism
- power law
- artificial neural networks
- graph transformation
- graph data
- minimum spanning tree
- graph layout
- graph theoretical
- connected dominating set
- spanning tree
- connected graphs
- edge weights
- inexact graph matching
- directed edges
- graph representations
- dense subgraphs
- real world graphs
- directed acyclic
- attributed graphs
- structured data
- reachability queries
- connected components
- probability distribution
- graph drawing
- proximity graph
- query graph
- maximum cardinality
- polynomial time complexity
- adjacency graph
- maximum clique
- random walk
- association graph
- planar graphs
- graph embedding
- neighborhood graph
- graph patterns
- small world
- graphical models
- directed acyclic graph
- topological information
- evolving graphs
- shortest path