9 citations · 10 across the 5 of their papers we have counts for
4 papers · 1 filter
Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise
Heather Mathews, Vaishakhi Mayya, Alexander Volfovsky +1
Community detection tasks have received a lot of attention across statistics, machine learning, and information theory with a large body of work concentrating on theoretical guaran…
Likelihood-based Inference for Partially Observed Epidemics on Dynamic Networks
Fan Bu, Allison E. Aiello, Jason Xu +1
We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, whi…
Interpretable Almost-Matching-Exactly With Instrumental Variables
M. Usaid Awan, Yameng Liu, Marco Morucci +3
Uncertainty in the estimation of the causal effect in observational studies is often due to unmeasured confounding, i.e., the presence of unobserved covariates linking treatments a…
The Geometry of Community Detection via the MMSE Matrix
Galen Reeves, Vaishakhi Mayya, Alexander Volfovsky
The information-theoretic limits of community detection have been studied extensively for network models with high levels of symmetry or homogeneity. The contribution of this paper…