81 citations · 116 across the 5 of their papers we have counts for
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math.ST2023
Learning cross-layer dependence structure in multilayer networks
Jiaheng Li, Jonathan R. Stewart
We propose a novel class of separable multilayer network models to capture cross-layer dependencies in multilayer networks, enabling the analysis of how interactions in one or more…
math.ST2020★ 3 cited
Pseudo-likelihood-based -estimation of random graphs with dependent edges and parameter vectors of increasing dimension
Jonathan R. Stewart, Michael Schweinberger
An important question in statistical network analysis is how to estimate models of discrete and dependent network data with intractable likelihood functions, without sacrificing co…
math.ST2017★ 32 cited
Concentration and consistency results for canonical and curved exponential-family models of random graphs
Michael Schweinberger, Jonathan Stewart
Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional…