Unsupervised pre-training of graph transformers on patient population graphs.
Chantal PellegriniNassir NavabAnees KaziPublished in: CoRR (2022)
Keyphrases
- graph representation
- graph theoretic
- directed graph
- graph theory
- graph structure
- graph mining
- graph structures
- graph model
- graph databases
- graph matching
- supervised learning
- weighted graph
- graph properties
- labeled graphs
- series parallel
- graph data
- graph theoretical
- graph partitioning
- graph construction
- graph classification
- adjacency matrix
- graph search
- graph clustering
- graph kernels
- random graphs
- graph isomorphism
- subgraph isomorphism
- spanning tree
- attributed graphs
- undirected graph
- structural pattern recognition
- graph drawing
- supervised training
- graph representations
- training set
- neighborhood graph
- directed acyclic
- adjacency graph
- connected graphs
- graph transformation
- maximum common subgraph
- bipartite graph
- semi supervised
- query graph
- unsupervised learning
- massive graphs
- web graph
- edge weights
- dynamic graph
- evolving graphs
- spinal cord injury
- finding the shortest path
- connected dominating set
- maximum clique
- frequent subgraphs
- pairwise
- real world graphs
- random walk
- structured data
- inexact graph matching
- normalized cut
- minimum spanning tree
- graph embedding
- graph layout
- topological information
- community discovery
- small world
- dense subgraphs
- reachability queries
- planar graphs
- polynomial time complexity