9 citations · 16 across the 6 of their papers we have counts for
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math.PR2017★ 9 cited
Mixing Time of Vertex-Weighted Exponential Random Graphs
Ryan DeMuse, Terry Easlick, Mei Yin
Exponential random graph models have become increasingly important in the study of modern networks ranging from social networks, economic networks, to biological networks. They see…
math.PR2017★ 3 cited
Phase Transitions in Edge-Weighted Exponential Random Graphs: Near-Degeneracy and Universality
Ryan DeMuse, Danielle Larcomb, Mei Yin
Conventionally used exponential random graphs cannot directly model weighted networks as the underlying probability space consists of simple graphs only. Since many substantively i…