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Data representation with optimal transport
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Optimal transport has been used to define bijective nonlinear transforms and different transport-related metrics for discriminating data and signals. Here we briefly describe the advances in this topic with the main applications and properties in each case.
Forward citations
Cited by 2 Pith papers
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Reduced Order Modeling of One-Dimensional Conservative PDEs via the Cumulative Distribution Transform
Mapping solution snapshots to mass-coordinate (CDT) space before POD compresses transport-dominated 1D conservative PDEs into far fewer modes, with proven Kolmogorov-width bounds.
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Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
The paper proves stability bounds for the max-normalized R-CDT under Wasserstein-infinity perturbations and introduces a mean-normalized R-CDT with Wasserstein-2 robustness guarantees for affinely transformed image classes.
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