Learning with minibatch Wasserstein : asymptotic and gradient properties

Learning with minibatch Wasserstein : asymptotic and gradient properties

9 October 2019

Rémi Gribonval

Papers citing "Learning with minibatch Wasserstein : asymptotic and gradient properties"

11 / 11 papers shown

Title
Model alignment using inter-modal bridges Ali Gholamzadeh Noor Sajid 93 0 0 18 May 2025
Spherical Tree-Sliced Wasserstein Distance Hoang V. Tran Thanh T. Chu K. Nguyen Trang Pham Tam Le Trung Quoc Nguyen OT 68 3 0 14 Mar 2025
Partial Distribution Matching via Partial Wasserstein Adversarial Networks Zi-Ming Wang Nan Xue Ling Lei Rebecka Jörnsten Gui-Song Xia OOD 76 0 0 16 Sep 2024
Submodular Framework for Structured-Sparse Optimal Transport Piyushi Manupriya Pratik Jawanpuria Karthik S. Gurumoorthy SakethaNath Jagarlapudi Bamdev Mishra OT 118 0 0 07 Jun 2024
Learning Generative Models across Incomparable Spaces Charlotte Bunne David Alvarez-Melis Andreas Krause Stefanie Jegelka GAN 41 112 0 14 May 2019
Interpolating between Optimal Transport and MMD using Sinkhorn Divergences Jean Feydy Thibault Séjourné François-Xavier Vialard S. Amari A. Trouvé Gabriel Peyré OT 45 524 0 18 Oct 2018
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 122 2,133 0 01 Mar 2018
Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance Jonathan Niles-Weed Francis R. Bach 108 417 0 01 Jul 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 119 9,509 0 31 Mar 2017
Sliced Wasserstein Kernels for Probability Distributions Soheil Kolouri Yang Zou Gustavo K. Rohde 26 159 0 10 Nov 2015
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 118 4,210 0 04 Jun 2013