Jun 28, 2021 · It can be cast as a multi-marginal optimal transport problem that allows efficient computation. Illustrative academic examples are presented.
Sep 13, 2024 · It can be cast as a multi-marginal optimal transport problem that allows efficient computation. Illustrative academic examples are presented.
Distribution-on-distribution regression with Wasserstein metric
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There are several advantages to using the Wasserstein metric: it gives more intuitive interpretations of mean and geodesics compared to other metrics, and it ...
Optimal transport (OT) and distributional robust optimisation (DRO) provide essential technical tools to all disciplines where stochastic optimisation and ...
We study the complexity of approximating the multimarginal optimal transport (MOT) distance, a generalization of the classical optimal transport distance, ...
Oct 22, 2024 · ... The optimal transport problem is a classic problem in mathematics that involves finding the most efficient way of moving mass to transform ...
Jun 10, 2023 · The proposed method uses multi-marginal optimal transport to enforce distributional constraints by minimizing the distance between probability ...
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This thesis deals with a class of multi-marginal optimal transport prob- lems, which we call graph-structured multi-marginal optimal transport. The.
The main idea of unbalanced op- timal transport is to regularize the objective function of optimal transport based on certain divergences be- tween marginal ...
Multi-marginal optimal transport (MOT) is a generalization of optimal transport theory to settings with possibly more than two marginals. The computation of ...