Results 11 to 20 of about 24,182 (212)
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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Fused Gromov-Wasserstein Distance for Structured Objects
Algorithms, 2020 Optimal transport theory has recently found many applications in machine learning thanks to its capacity to meaningfully compare various machine learning objects that are viewed as distributions.
Titouan Vayer +4 more
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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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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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Well-posedness of a parabolic moving-boundary problem in the setting of Wasserstein gradient flows [PDF]
, 2010 We develop a gradient-flow framework based on the Wasserstein metric for a parabolic moving-boundary problem that models crystal dissolution and precipitation. In doing so we derive a new weak formulation for this moving-boundary problem and we show that
Peletier, Mark A., Portegies, Jacobus W.
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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 generalization of Hausdorff dimension applied to Hilbert cubes and Wasserstein spaces [PDF]
, 2012 A Wasserstein spaces is a metric space of sufficiently concentrated probability measures over a general metric space. The main goal of this paper is to estimate the largeness of Wasserstein spaces, in a sense to be precised.
BENOÎT KLOECKNER +6 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
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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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Joint geoacoustic inversion based on Pearson correlation coefficient constraints [PDF]
JASA Express Letters, 2023 This Letter proposes a joint geoacoustic inversion method for modal group velocity dispersion and amplitudes of waveform by incorporating a Pearson correlation constraint. Numerical simulations show that this joint inversion leads to improved geoacoustic
Jiaqi Ding, Xiaofeng Zhao, Pinglv Yang
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