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On a Linear Gromov–Wasserstein Distance

  • Published:2022 Issue: Volume:31 Page:7292-7305
  • ISSN:1057-7149
  • Container-title:IEEE Transactions on Image Processing
  • language:
  • Short-container-title:IEEE Trans. on Image Process.

Author:

Beier Florian1ORCID,Beinert Robert1ORCID,Steidl Gabriele1ORCID

Affiliation:

1. Institute of Mathematics, Technische Universität Berlin, Berlin, Germany

Funder

German Research Foundation (DFG) within the Research Training Group (RTG) 2433 DAEDALUS

Federal Ministry of Education and Research [Bundesministerium für Bildung und Forschung (BMBF)] Project “VI-Screen”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Reference42 articles.

1. Optimal transport for structured data with application on graphs;vayer;Proc 36th Int Conf Mach Learn,2019

2. Supervised Learning by Support Vector Machines

3. Exploring network structure, dynamics, and function using NetworkX;hagberg;Proc 7th Python Sci Conf,2008

4. Scikit-learn: Machine learning in Python;pedregosa;J Mach Learn Res,2011

5. POT: Python optimal transport;flamary;J Mach Learn Res,2021

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1. Parallelly Sliced Optimal Transport on Spheres and on the Rotation Group;Journal of Mathematical Imaging and Vision;2024-07-26

2. Multi-marginal Gromov–Wasserstein transport and barycentres;Information and Inference: A Journal of the IMA;2023-09-18

3. Sliced optimal transport on the sphere;Inverse Problems;2023-08-30

4. On Assignment Problems Related to Gromov–Wasserstein Distances on the Real Line;SIAM Journal on Imaging Sciences;2023-06-23

5. Simple approximative algorithms for free-support Wasserstein barycenters;Computational Optimization and Applications;2023-03-01
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