Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs

2 June 2021

Papers citing "Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs"

23 / 23 papers shown

Title
Model alignment using inter-modal bridges Ali Gholamzadeh Noor Sajid 183 0 0 18 May 2025
The Z-Gromov-Wasserstein Distance Martin Bauer Facundo Mémoli Tom Needham Mao Nishino OT 55 2 0 15 Aug 2024
Quantized Gromov-Wasserstein Samir Chowdhury David W. Miller Tom Needham 36 26 0 05 Apr 2021
Low-Rank Sinkhorn Factorization M. Scetbon Marco Cuturi Gabriel Peyré 50 59 0 08 Mar 2021
Linear Time Sinkhorn Divergences using Positive Features M. Scetbon Marco Cuturi 76 26 0 12 Jun 2020
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang Gabriel Peyré M. Fadili Marcelo Pereyra 49 66 0 11 Feb 2020
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces Ryoma Sato Marco Cuturi M. Yamada H. Kashima 95 23 0 05 Feb 2020
MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data Andrew J. Blumberg Mathieu Carrière Michael A. Mandell R. Rabadán Soledad Villar 23 14 0 06 Jan 2020
Multi-subject MEG/EEG source imaging with sparse multi-task regression H. Janati Yonas T. Tadesse Bertrand Thirion Marco Cuturi Alexandre Gramfort 92 32 0 03 Oct 2019
Sample-Optimal Low-Rank Approximation of Distance Matrices Piotr Indyk A. Vakilian Tal Wagner David P. Woodruff 27 36 0 02 Jun 2019
Sliced Gromov-Wasserstein Titouan Vayer Rémi Flamary Romain Tavenard Laetitia Chapel Nicolas Courty OT 46 100 0 24 May 2019
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching Hongteng Xu Dixin Luo Lawrence Carin 55 194 0 18 May 2019
Learning Generative Models across Incomparable Spaces Charlotte Bunne David Alvarez-Melis Andreas Krause Stefanie Jegelka GAN 50 112 0 14 May 2019
Gromov-Wasserstein Learning for Graph Matching and Node Embedding Hongteng Xu Dixin Luo H. Zha Lawrence Carin 87 259 0 17 Jan 2019
Massively scalable Sinkhorn distances via the Nyström method Jason M. Altschuler Francis R. Bach Alessandro Rudi Jonathan Niles-Weed 46 109 0 12 Dec 2018
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties David Tellez G. Litjens J. A. van der Laak R. Tavenard F. Ciompi OT 75 127 0 07 Nov 2018
Unsupervised Hyperalignment for Multilingual Word Embeddings J. Alaux Edouard Grave Marco Cuturi Armand Joulin 52 71 0 02 Nov 2018
Statistical Optimal Transport via Factored Couplings Aden Forrow Jan-Christian Hütter Mor Nitzan Philippe Rigollet Geoffrey Schiebinger Jonathan Niles-Weed OT 138 69 0 19 Jun 2018
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 199 2,143 0 01 Mar 2018
Word Translation Without Parallel Data Alexis Conneau Guillaume Lample MarcÁurelio Ranzato Ludovic Denoyer Hervé Jégou 284 1,655 0 11 Oct 2017
Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance Jonathan Niles-Weed Francis R. Bach 179 421 0 01 Jul 2017
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration Jason M. Altschuler Jonathan Niles-Weed Philippe Rigollet OT 66 590 0 26 May 2017
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 194 4,251 0 04 Jun 2013