Bayesian Inference for Optimal Transport with Stochastic Cost

In machine learning and computer vision, optimal transport has had significant success in learning generative models and defining metric distances between structured and stochastic data objects, that can be cast as probability measures. The key element of optimal transport is the so called lifting o...

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Veröffentlicht in:	arXiv.org 2020-10
Hauptverfasser:	Mallasto, Anton, Heinonen, Markus, Kaski, Samuel
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian analysis Computer vision Machine learning Operating costs Probability theory Statistical inference Traffic flow Transportation planning
Online-Zugang:	Volltext
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