Entropic Optimal Transport in Random Graphs. (arXiv:2201.03949v1 [stat.ML])

In graph analysis, a classic task consists in computing similarity measures
between (groups of) nodes. In latent space random graphs, nodes are associated
to unknown latent variables. One may then seek to compute distances directly in
the latent space, using only the graph structure. In this paper, we show that
it is possible to consistently estimate entropic-regularized Optimal Transport
(OT) distances between groups of nodes in the latent space. We provide a
general stability result for entropic OT with respect …

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