A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings.
Michael ScholkemperDamin KühnGerion NabbefeldSimon MusallBjörn KampaMichael T. SchaubPublished in: CoRR (2024)
Keyphrases
- graph structure
- directed graph
- distance measure
- undirected graph
- bayesian networks
- probability distribution
- random walk
- root node
- edge weights
- overlapping communities
- graph mining
- path length
- graph model
- euclidean space
- finding the shortest path
- graph theory
- graph representation
- graph theoretic
- graph matching
- generative model
- dimensionality reduction
- probabilistic model
- information theoretic
- graph databases
- low dimensional
- graph clustering
- graph partitioning
- connected components
- directed acyclic graph
- weighted graph
- posterior probability
- probabilistic reasoning
- strongly connected
- probability measure
- similarity measure
- structured data
- outlier detection
- bipartite graph
- joint distribution
- vector space
- belief networks