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The Wasserstein distances

2009
Assume, as before, that you are in charge of the transport of goods between producers and consumers, whose respective spatial distributions are modeled by probability measures.
openaire   +1 more source

Wasserstein Distance and the Distributionally Robust TSP

Operations Research, 2018
One of the most common strategies used in large-scale logistics problems is districting, in which one divides a service region into smaller pieces. This is particularly useful when one does not know the true locations of demand, but has only limited information such as a probability distribution or a small set of sample data.
John Gunnar Carlsson   +2 more
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Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance.

CoRR
In this paper, we investigate the properties of the Sliced Wasserstein Distance (SW) when employed as an objective functional. The SW metric has gained significant interest in the optimal transport and machine learning literature, due to its ability to capture intricate geometric properties of probability distributions while remaining computationally ...
Vauthier, Christophe   +2 more
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Convergence in the Wasserstein Distance

2018
In the previous chapters, we obtained rates of convergence in the total variation distance of the iterates \(P^n\) of an irreducible positive Markov kernel P to its unique invariant measure \(\pi \) for \(\pi \)-almost every \(x \in \mathsf {X}\) and for all \(x \in \mathsf {X}\) if the kernel P is irreducible and positive Harris recurrent. Conversely,
Randal Douc   +3 more
openaire   +1 more source

An extended Exp-TODIM method for multiple attribute decision making based on the Z-Wasserstein distance

Expert Systems With Applications, 2023
Guiwu Wei, Zhiwen Mo, Hong Sun
exaly  

Fault Diagnosis of Rotating Machinery Based on Wasserstein Distance and Feature Selection

IEEE Transactions on Automation Science and Engineering, 2022
Andrea Monteriù   +2 more
exaly  

Minimax estimation of smooth densities in Wasserstein distance

Annals of Statistics, 2022
Jonathan Niles-Weed
exaly  

Estimating processes in adapted Wasserstein distance

Annals of Applied Probability, 2022
Mathias Beiglböck, Daniel Bartl
exaly  

Mckean-Vlasov sdes with drifts discontinuous under wasserstein distance

Discrete and Continuous Dynamical Systems, 2021
Feng-Yu Wang
exaly  

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