muxGNN: Multiplex Graph Neural Network for Heterogeneous Graphs.
Joshua MeltonSiddharth KrishnanPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2023)
Keyphrases
- neural network
- graph representation
- directed graph
- graph theory
- graph databases
- graph matching
- graph structure
- graph mining
- graph construction
- graph theoretic
- labeled graphs
- adjacency matrix
- graph structures
- graph model
- graph properties
- graph clustering
- weighted graph
- graph theoretical
- graph classification
- series parallel
- graph isomorphism
- spanning tree
- graph search
- random graphs
- graph partitioning
- bipartite graph
- graph data
- structural pattern recognition
- undirected graph
- subgraph isomorphism
- maximum clique
- evolving graphs
- inexact graph matching
- edge weights
- dynamic graph
- graph representations
- disk resident
- graph kernels
- average degree
- connected graphs
- planar graphs
- graph transformation
- adjacency graph
- graph patterns
- knn
- minimum spanning tree
- maximum cardinality
- connected dominating set
- dense subgraphs
- social graphs
- random walk
- maximum common subgraph
- graph drawing
- finding the shortest path
- reachability queries
- attributed graphs
- massive graphs
- web graph
- directed acyclic graph
- association graph
- proximity graph
- graph layout
- maximal cliques
- quasi cliques
- real world graphs
- structured data
- neural network model
- small world
- frequent subgraphs
- bounded treewidth
- query graph
- hyper graph
- polynomial time complexity
- community discovery
- graph embedding
- directed acyclic
- strongly connected
- neighborhood graph
- connected components
- pattern mining
- maximum independent set
- shortest path
- social networks