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