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Unlocking Geodesic Gromov-Wasserstein Distances for 3D Modeling

Choromanski, Krzysztof Marcin et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognitiondata-structures-and-algorithms
\textit{Gromov-Wasserstein Distances} (GWDs) provide quantitative ways of comparing probabilistic distributions defined on different metric spaces by applying techniques from the optimal transport theory. As such, GWD can be potentially useful in a large variety of applications ranging from graph ma
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