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Found 6 papers, 3 papers with code
SMGRL: Scalable Multi-resolution Graph Representation Learning
The resulting multi-resolution embeddings can be aggregated to yield high-quality node embeddings that capture both long- and short-range dependencies.
On Evaluation Metrics for Graph Generative Models
While we focus on applying these metrics to GGM evaluation, in practice this enables the ability to easily compute the dissimilarity between any two sets of graphs regardless of domain.
Building LEGO Using Deep Generative Models of Graphs
Generative models are now used to create a variety of high-quality digital artifacts.
A Nonparametric Bayesian Model for Sparse Dynamic Multigraphs
As the availability and importance of temporal interaction data--such as email communication--increases, it becomes increasingly important to understand the underlying structure that underpins these interactions.
Sequential Edge Clustering in Temporal Multigraphs
Interaction graphs, such as those recording emails between individuals or transactions between institutions, tend to be sparse yet structured, and often grow in an unbounded manner.
Dynamic Network Model from Partial Observations
We propose a novel framework for providing a non-parametric dynamic network model--based on a mixture of coupled hierarchical Dirichlet processes-- based on data capturing cascade node infection times.
