73 citations · 134 across the 7 of their papers we have counts for
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cs.LG2019
Universal Invariant and Equivariant Graph Neural Networks
Nicolas Keriven, Gabriel Peyré
Graph Neural Networks (GNN) come in many flavors, but should always be either invariant (permutation of the nodes of the input graph does not affect the output) or equivariant (per…
cs.LG2018
Semi-dual Regularized Optimal Transport
Marco Cuturi, Gabriel Peyré
Variational problems that involve Wasserstein distances and more generally optimal transport (OT) theory are playing an increasingly important role in data sciences. Such problems…