Graph limit theory provides a rigorous framework for analysing sequences of large graphs by representing them as continuous objects known as graphons – symmetric measurable functions on the unit ...

Nov. 30, 2023 — David Tench, the 2023 Grace Hopper postdoctoral fellow at Lawrence Berkeley National Laboratory (Berkeley Lab), describes discovering his fellowship opportunity as a “Goldilocks moment ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 79, No. 5 (NOVEMBER 2017), pp. 1295-1366 (72 pages) Statistical network modelling has focused on representing the ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...

We study the asymptotics for sparse exponential random graph models where the parameters may depend on the number of vertices of the graph. We obtain exact estimates for the mean and variance of the ...