Neural Optimal Transport with General Cost Functionals
Neural Optimal Transport with General Cost Functionals
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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We introduce a novel neural network-based algorithm to compute optimal transport (OT) plans for general cost functionals. In contrast to common Euclidean costs, i.e., \(\ell^1\) or \(\ell^2\), such functionals provide more flexibility and allow using auxiliary information, such as class labels, to construct the required transport map. Existing meth...
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Neural Optimal Transport with General Cost Functionals
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TN_cdi_proquest_journals_2672172483
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2672172483
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2331-8422
