Highly Scalable Maximum Likelihood and Conjugate Bayesian Inference for ERGMs on Graph Sets with Equivalent Vertices.
Fan YinCarter T. ButtsPublished in: CoRR (2021)
Keyphrases
- bayesian inference
- highly scalable
- maximum likelihood
- hyperparameters
- weighted graph
- probabilistic model
- prior information
- labeled graphs
- undirected graph
- adjacency matrix
- edge weights
- bayesian model
- variational bayes
- random graphs
- statistical inference
- variational inference
- strongly connected
- attributed graphs
- directed edges
- gaussian process
- directed graph
- parameter estimation
- expectation maximization
- planar graphs
- web caching
- hierarchical bayesian
- gibbs sampler
- expectation propagation
- hidden variables
- query graph
- particle filter
- posterior distribution
- mixture model
- vertex set
- bayesian models
- graph structure
- markov chain monte carlo
- em algorithm
- spanning tree
- maximum a posteriori
- gaussian distribution
- graph partitioning
- bayesian methods
- decision trees