GraphAlign: Pretraining One Graph Neural Network on Multiple Graphs via Feature Alignment.
Zhenyu HouHaozhan LiYukuo CenJie TangYuxiao DongPublished in: CoRR (2024)
Keyphrases
- neural network
- graph theory
- graph structure
- graph representation
- graph theoretic
- directed graph
- graph matching
- graph construction
- graph model
- graph databases
- weighted graph
- graph mining
- random graphs
- labeled graphs
- graph transformation
- artificial neural networks
- graph partitioning
- undirected graph
- back propagation
- bipartite graph
- graph data
- graph classification
- graph structures
- adjacency matrix
- graph theoretical
- graph kernels
- graph clustering
- random walk
- graph properties
- polynomial time complexity
- structured data
- graph isomorphism
- subgraph isomorphism
- graph search
- reachability queries
- structural pattern recognition
- neural network model
- finding the shortest path
- dynamic graph
- connected dominating set
- similarity graph
- attributed graphs
- graph embedding
- neighborhood graph
- edge weights
- connected components
- pairwise