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Related papers: Partial Gromov-Wasserstein Metric

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The properties of gravitational-wave (GW) propagation are modified in alternative theories of gravity and are crucial observables to test gravity at cosmological distance. The propagation speed has already been measured from GW170817 so…

General Relativity and Quantum Cosmology · Physics 2019-05-22 Atsushi Nishizawa , Shun Arai

Gravitational-wave (GW) scattering in strong gravitational fields is a central problem in GW lensing. Yet, conventional treatments based on asymptotic expansions suffer from divergences and become unreliable near the optical axis. In this…

General Relativity and Quantum Cosmology · Physics 2026-01-01 Zhao Li , Shaoqi Hou , Wen Zhao

Peccati, Sole, Taqqu, and Utzet recently combined Stein's method and Malliavin calculus to obtain a bound for the Wasserstein distance of a Poisson functional and a Gaussian random variable. Convergence in the Wasserstein distance always…

Probability · Mathematics 2014-09-09 Matthias Schulte

In testing gravity a model-independent way, one of crucial tests is measuring the propagation speed of a gravitational wave (GW). In general relativity, a GW propagates with the speed of light, while in the alternative theories of gravity…

General Relativity and Quantum Cosmology · Physics 2016-06-22 Atsushi Nishizawa

Strong gravitational lensing by galaxies provides us with a unique opportunity to understand the nature of gravity on galactic and extra-galactic scales. In this paper, we propose a new multimessenger approach using data from both…

Cosmology and Nongalactic Astrophysics · Physics 2020-07-08 Tao Yang , Bin Hu , Rong-Gen Cai , Bin Wang

A new weak Galerkin (WG) finite element method for solving the second-order elliptic problems on polygonal meshes by using polynomials of boundary continuity is introduced and analyzed. The WG method is utilizing weak functions and their…

Numerical Analysis · Mathematics 2015-09-30 Qilong Zhai , Xiu Ye , Ruishu Wang , Ran Zhang

Given two point sets, the problem of registration is to recover a transformation that matches one set to the other. This task is challenging due to the presence of the large number of outliers, the unknown non-rigid deformations and the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-07 Zi-Ming Wang , Nan Xue , Ling Lei , Gui-Song Xia

In recent years, machine learning (ML) methods have become increasingly popular in wireless communication systems for several applications. A critical bottleneck for designing ML systems for wireless communications is the availability of…

Signal Processing · Electrical Eng. & Systems 2025-06-03 Satyavrat Wagle , Akshay Malhotra , Shahab Hamidi-Rad , Aditya Sant , David J. Love , Christopher G. Brinton

It has been shown in the literature that detections of gravitational waves (GWs) emitted by binary sources can provide measurements of luminosity distance. The events followed by electromagnetic counterparts are, then, suitable for probing…

Cosmology and Nongalactic Astrophysics · Physics 2022-03-16 Isabela S. Matos

Rapidly estimating the remaining wall thickness (RWT) is paramount for the non-destructive condition assessment evaluation of large critical metallic pipelines. A robotic vehicle with embedded magnetism-based sensors has been developed to…

Machine Learning · Computer Science 2019-07-03 Linh Nguyen , Jaime Valls Miro , Lei Shi , Teresa Vidal-Calleja

We investigate mismatched estimation in the context of the distance geometry problem (DGP). In the DGP, for a set of points, we are given noisy measurements of pairwise distances between the points, and our objective is to determine the…

Signal Processing · Electrical Eng. & Systems 2022-06-14 Mahmoud Abdelkhalek , Dror Baron , Chau-Wai Wong

This paper introduces a novel and generic framework to solve the flagship task of supervised labeled graph prediction by leveraging Optimal Transport tools. We formulate the problem as regression with the Fused Gromov-Wasserstein (FGW) loss…

Machine Learning · Statistics 2022-06-27 Luc Brogat-Motte , Rémi Flamary , Céline Brouard , Juho Rousu , Florence d'Alché-Buc

Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate methods have been used to resolve the issue in practice,…

Machine Learning · Statistics 2017-09-13 Sungsoo Ahn , Michael Chertkov , Jinwoo Shin

Gravitational Waves (GWs) provide a powerful means for cosmological distance estimation, circumventing the systematic uncertainties associated with traditional electromagnetic (EM) indicators. This work presents a model for estimating…

General Relativity and Quantum Cosmology · Physics 2025-08-14 Trisha V , Rakesh V , Arun Kenath

Wasserstein distance (WD) and the associated optimal transport plan have been proven useful in many applications where probability measures are at stake. In this paper, we propose a new proxy of the squared WD, coined min-SWGG, that is…

Machine Learning · Statistics 2023-10-31 Guillaume Mahey , Laetitia Chapel , Gilles Gasso , Clément Bonet , Nicolas Courty

We propose the Wasserstein-Fourier (WF) distance to measure the (dis)similarity between time series by quantifying the displacement of their energy across frequencies. The WF distance operates by calculating the Wasserstein distance between…

Machine Learning · Statistics 2020-12-14 Elsa Cazelles , Arnaud Robert , Felipe Tobar

We investigate the constraint ability of the gravitational wave (GW) as the standard siren on the cosmological parameters by using the third-generation gravitational wave detector: the Einstein Telescope. We simulate the luminosity…

Cosmology and Nongalactic Astrophysics · Physics 2017-02-21 Rong-Gen Cai , Tao Yang

Weak Galerkin (WG) refers to general finite element methods for partial differential equations in which differential operators are approximated by weak forms through the usual integration by parts. In particular, WG methods allow the use of…

Numerical Analysis · Mathematics 2011-11-04 Lin Mu , Junping Wang , Xiu Ye , Shan Zhao

In this paper we introduce a Wasserstein-type distance on the set of Gaussian mixture models. This distance is defined by restricting the set of possible coupling measures in the optimal transport problem to Gaussian mixture models. We…

Optimization and Control · Mathematics 2020-06-15 Julie Delon , Agnes Desolneux

The Wasserstein barycenter problem seeks a probability measure that minimizes the weighted average of the Wasserstein distances to a given collection of probability measures. We study the discrete setting, where each measure has finite…

Optimization and Control · Mathematics 2025-11-07 Jiaqi Wang , Weijun Xie