A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings.
Michael ScholkemperDamin KühnGerion NabbefeldSimon MusallBjörn KampaMichael T. SchaubPublished in: ICASSP (2024)
Keyphrases
- graph structure
- directed graph
- undirected graph
- graph model
- distance measure
- power law
- random walk
- degree distribution
- graph representation
- finding the shortest path
- probability distribution
- bayesian networks
- probabilistic model
- pointwise
- random variables
- probability measure
- root node
- weighted graph
- connected components
- nodes of a graph
- graph theory
- bipartite graph
- vector space
- generative model
- structured data
- hilbert space
- path length
- low dimensional
- edge weights
- betweenness centrality
- tree structure
- mixture distributions
- information theoretic
- similarity measure
- data streams
- overlapping communities
- source node
- feature vectors
- dimensionality reduction
- strongly connected
- graphical models
- graph partitioning
- spanning tree
- graph matching
- manifold learning