6 papers
Conformal Prediction for Dyadic Regression Under Complex Missingness
Robert Lunde, Minjie Yang, Elizaveta Levina +1
We develop a framework for conformal prediction in dyadic regression problems under complex missingness mechanisms. At the theoretical level, we develop general technical tools for…
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 grouped multiplex networks
Alexander Kagan, Peter W. MacDonald, Elizaveta Levina +1
Complex multilayer network datasets have become ubiquitous in various applications, including neuroscience, social sciences, economics, and genetics. Notable examples include brain…
Flexible Modeling of Information Diffusion on Networks with Statistical Guarantees
Alexander Kagan, Elizaveta Levina, Ji Zhu
Modeling information spread through a network is one of the key problems of network analysis, with applications in a wide array of areas such as marketing and public health. Most a…
Interpretable Network-assisted Random Forest+
Tiffany M. Tang, Elizaveta Levina, Ji Zhu
Machine learning algorithms often assume that training samples are independent. When data points are connected by a network, the induced dependency between samples is both a challe…
Heterogeneous Treatment Effects under Network Interference: A Nonparametric Approach Based on Node Connectivity
Heejong Bong, Colin B. Fogarty, Elizaveta Levina +1
In network settings, interference between units makes causal inference more challenging as outcomes may depend on the treatments received by others in the network. Typical estimand…