Results 41 to 50 of about 2,509,053 (235)
Convolutional wasserstein distances [PDF]
ACM Transactions on Graphics, 2015 This paper introduces a new class of algorithms for optimization problems involving optimal transportation over geometric domains. Our main contribution is to show that optimal transportation can be made tractable over large domains used in graphics, such as images and triangle meshes, improving performance by orders of magnitude compared to previous ...
Solomon, Justin +7 more
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Minimum entropy production, detailed balance and Wasserstein distance for continuous-time Markov processes [PDF]
Journal of Physics A: Mathematical and Theoretical, 2021 We investigate the problem of minimizing the entropy production for a physical process that can be described in terms of a Markov jump dynamics. We show that, without any further constraints, a given time-evolution may be realized at arbitrarily small ...
A. Dechant
semanticscholar +1 more source
Gromov–Wasserstein distances between Gaussian distributions
Journal of Applied Probability, 2022 AbstractGromov–Wasserstein distances were proposed a few years ago to compare distributions which do not lie in the same space. In particular, they offer an interesting alternative to the Wasserstein distances for comparing probability measures living on Euclidean spaces of different dimensions. We focus on the Gromov–Wasserstein distance with a ground
Salmona, Antoine +2 more
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Free complete Wasserstein algebras [PDF]
Logical Methods in Computer Science, 2018 We present an algebraic account of the Wasserstein distances $W_p$ on complete metric spaces, for $p \geq 1$. This is part of a program of a quantitative algebraic theory of effects in programming languages.
Radu Mardare +2 more
doaj +1 more source
Hydrological objective functions and ensemble averaging with the Wasserstein distance
Hydrology and Earth System Sciences, 2023 . When working with hydrological data, the ability to quantify the similarity of different datasets is useful. The choice of how to make this quantification has a direct influence on the results, with different measures of similarity emphasising ...
Jared C. Magyar, M. Sambridge
semanticscholar +1 more source
Convergence of the empirical measure in expected Wasserstein distance: non asymptotic explicit bounds in Rd [PDF]
E S A I M: Probability & Statistics, 2022 . We provide some non asymptotic bounds, with explicit constants, that measure the rate of convergence, in expected Wasserstein distance, of the empirical measure associated to an i.i.d. N -sample of a given probability distribution on R d .
N. Fournier
semanticscholar +1 more source
On a Linear Gromov–Wasserstein Distance
IEEE Transactions on Image Processing, 2022 Gromov-Wasserstein distances are generalization of Wasserstein distances, which are invariant under distance preserving transformations. Although a simplified version of optimal transport in Wasserstein spaces, called linear optimal transport (LOT), was successfully used in practice, there does not exist a notion of linear Gromov-Wasserstein distances ...
Florian Beier +2 more
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Big Data and Cognitive Computing, 2022 Large retail companies routinely gather huge amounts of customer data, which are to be analyzed at a low granularity. To enable this analysis, several Key Performance Indicators (KPIs), acquired for each customer through different channels are associated
Andrea Ponti +4 more
doaj +1 more source
Generalized Wasserstein distance and its application to transport equations with source [PDF]
, 2012 In this article, we generalize the Wasserstein distance to measures with different masses. We study the properties of such distance. In particular, we show that it metrizes weak convergence for tight sequences.
A. Figalli +17 more
core +4 more sources
Tanaka Theorem for Inelastic Maxwell Models [PDF]
, 2006 We show that the Euclidean Wasserstein distance is contractive for inelastic homogeneous Boltzmann kinetic equations in the Maxwellian approximation and its associated Kac-like caricature.
A. Pulvirenti +29 more
core +4 more sources