Results 11 to 20 of about 3,027 (198)
Deconvolution for the Wasserstein metric and geometric inference [PDF]
Electronic Journal of Statistics, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Caillerie, Claire +3 more
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A prelude to statistics in Wasserstein metric spaces
Asian Journal of Economics and Banking, 2023 PurposeThis paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory ...
Chon Van Le, Uyen Hoang Pham
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Remote Sensing, 2023 The inversion of acoustic field data to estimate geoacoustic parameters has been a prominent research focus in the field of underwater acoustics for several decades.
Jiaqi Ding +3 more
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The Wasserstein metric in Factor Analysis [PDF]
, 2013 We consider the problem of approximating a (nonnegative definite) covariance matrix by the sum of two structured covariances –one which is diagonal and one which has low-rank. Such an additive decomposition follows the dictum of factor analysis where linear relations are sought between variables corrupted by independent measurement noise.
Lipeng Ning, Tryphon T. Georgiou
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The exponential formula for the wasserstein metric [PDF]
ESAIM: Control, Optimisation and Calculus of Variations, 2016 Many evolutionary partial differential equations may be rewritten as the gradient flow of an energy functional, a perspective which provides useful estimates on the behavior of solutions. The notion of gradient flow requires both the specification of an energy functional and a metric with respect to which the gradient is taken.
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Open-Set Signal Recognition Based on Transformer and Wasserstein Distance
Applied Sciences, 2023 Open-set signal recognition provides a new approach for verifying the robustness of models by introducing novel unknown signal classes into the model testing and breaking the conventional closed-set assumption, which has become very popular in real-world
Wei Zhang +4 more
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Optimal Transport for Gaussian Mixture Models
IEEE Access, 2019 We introduce an optimal mass transport framework on the space of Gaussian mixture models. These models are widely used in statistical inference. Specifically, we treat the Gaussian mixture models as a submanifold of probability densities equipped with ...
Yongxin Chen +2 more
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The quadratic Wasserstein metric for inverse data matching [PDF]
Inverse Problems, 2020 Abstract This work characterizes, analytically and numerically, two major effects of the quadratic Wasserstein ( W 2 ) distance as the measure of data discrepancy in computational solutions of inverse problems.
Björn Engquist, Kui Ren, Yunan Yang
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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
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Wasserstein distance and metric trees
L’Enseignement Mathématique, 2023 We study the Wasserstein (or earthmover) metric on the space P(X) of probability measures on a metric space X . We show that, if a finite metric space
Mathey-Prevot, Maxime, Valette, Alain
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