24 citations · 35 across the 14 of their papers we have counts for
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stat.ML2022★ 24 cited
Not too little, not too much: a theoretical analysis of graph (over)smoothing
Nicolas Keriven
We analyze graph smoothing with \emph{mean aggregation}, where each node successively receives the average of the features of its neighbors. Indeed, it has quickly been observed th…
stat.ML2022★ 1 cited
Entropic Optimal Transport in Random Graphs
Nicolas Keriven
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 variabl…