Generalizing Graph Convolutional Neural Networks with Edge-Variant Recursions on Graphs.
Elvin IsufiFernando GamaAlejandro RibeiroPublished in: CoRR (2019)
Keyphrases
- weighted graph
- convolutional neural networks
- undirected graph
- edge weights
- graph structure
- graph theory
- graph matching
- vertex set
- adjacency matrix
- graph representation
- graph model
- graph partitioning
- directed graph
- graph clustering
- subgraph isomorphism
- labeled graphs
- graph construction
- shortest path
- graph search
- graph mining
- bipartite graph
- random graphs
- graph theoretic
- disjoint paths
- minimum spanning tree
- graph databases
- spanning tree
- graph theoretical
- graph structures
- series parallel
- strongly connected
- densely connected
- graph data
- graph classification
- graph transformation
- dynamic graph
- adjacency graph
- directed acyclic
- evolving graphs
- inexact graph matching
- convolutional network
- neighborhood graph
- graph kernels
- dense subgraphs
- maximum common subgraph
- edge detection
- random walk
- small world
- graph properties
- maximum clique
- planar graphs
- reachability queries
- structural pattern recognition
- real world graphs
- finding the shortest path
- approximation algorithms
- web graph
- connected dominating set
- social networks
- complex networks
- massive graphs
- strongly connected components
- directed acyclic graph
- proximity graph
- graph representations
- graph isomorphism