This paper provides a selective review of the statistical network analys...
The recent explosion of genetic and high dimensional biobank and 'omic' ...
Spectral embedding finds vector representations of the nodes of a networ...
This paper considers the graph signal processing problem of anomaly dete...
Both observed and unobserved vertex heterogeneity can influence block
st...
In many applications of network analysis, it is important to distinguish...
The development of models for multiple heterogeneous network data is of
...
Clustering is concerned with coherently grouping observations without an...
We propose a Bayesian methodology for estimating spiked covariance matri...
Statistical inference on graphs often proceeds via spectral methods invo...
Estimating eigenvectors and low-dimensional subspaces is of central
impo...