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Found 5 papers, 0 papers with code
Variational Inference: Posterior Threshold Improves Network Clustering Accuracy in Sparse Regimes
Variational inference has been widely used in machine learning literature to fit various Bayesian models.
Network Estimation by Mixing: Adaptivity and More
While many methods have been proposed to address this problem in recent years, they usually assume that the true model belongs to a known class, which is not verifiable in most real-world applications.
Linear regression and its inference on noisy network-linked data
Linear regression on network-linked observations has been an essential tool in modeling the relationship between response and covariates with additional network structures.
Methodology
Estimating the number of communities in networks by spectral methods
Community detection is a fundamental problem in network analysis with many methods available to estimate communities.
Optimization via Low-rank Approximation for Community Detection in Networks
Community detection is one of the fundamental problems of network analysis, for which a number of methods have been proposed.
