154 citations · 195 across the 13 of their papers we have counts for
6 papers · 1 filter
Mesoscale two-sample testing for networks
Peter W. MacDonald, Elizaveta Levina, Ji Zhu
Networks arise naturally in many scientific fields as a representation of pairwise connections. Statistical network analysis has most often considered a single large network, but i…
Latent space models for multiplex networks with shared structure
Peter W. MacDonald, Elizaveta Levina, Ji Zhu
Latent space models are frequently used for modeling single-layer networks and include many popular special cases, such as the stochastic block model and the random dot product gra…
Fast Network Community Detection with Profile-Pseudo Likelihood Methods
Jiangzhou Wang, Jingfei Zhang, Binghui Liu +2
The stochastic block model is one of the most studied network models for community detection. It is well-known that most algorithms proposed for fitting the stochastic block model…
Community models for networks observed through edge nominations
Tianxi Li, Elizaveta Levina, Ji Zhu
Communities are a common and widely studied structure in networks, typically under the assumption that the network is fully and correctly observed. In practice, network data are of…
Generalized linear models with low rank effects for network data
Yun-Jhong Wu, Elizaveta Levina, Ji Zhu
Networks are a useful representation for data on connections between units of interests, but the observed connections are often noisy and/or include missing values. One common appr…
A new approach to Cholesky-based covariance regularization in high dimensions
Adam J. Rothman, Elizaveta Levina, Ji Zhu
In this paper we propose a new regression interpretation of the Cholesky factor of the covariance matrix, as opposed to the well known regression interpretation of the Cholesky fac…