Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities.
Antonio LongaVeronica LachiGabriele SantinMonica BianchiniBruno LepriPietro LiòFranco ScarselliAndrea PasseriniPublished in: CoRR (2023)
Keyphrases
- neural network
- weighted graph
- graph representation
- graph theoretic
- graph structure
- graph construction
- graph matching
- graph theory
- graph databases
- labeled graphs
- graph mining
- graph model
- graph clustering
- graph classification
- directed graph
- adjacency matrix
- series parallel
- graph properties
- graph theoretical
- random graphs
- undirected graph
- graph structures
- bipartite graph
- subgraph isomorphism
- graph data
- graph search
- disk resident
- structural pattern recognition
- graph kernels
- graph partitioning
- dynamic graph
- graph representations
- graph transformation
- pattern recognition
- spanning tree
- maximum common subgraph
- graph isomorphism
- minimum spanning tree
- graph drawing
- planar graphs
- evolving graphs
- edge weights
- graph layout
- artificial neural networks
- directed acyclic
- finding the shortest path
- reachability queries
- frequent subgraphs
- temporal reasoning
- structured data
- connected graphs
- real world graphs
- connected dominating set
- back propagation
- average degree
- social graphs
- maximum clique
- temporal sequences
- attributed graphs
- topological information
- graph patterns
- temporal information
- neighborhood graph
- inexact graph matching
- small world
- maximum cardinality
- community discovery
- maximal cliques
- dense subgraphs
- random walk
- vertex set
- query graph
- temporal patterns
- massive graphs
- graph embedding
- polynomial time complexity
- connected components
- pattern mining