v1v2 (latest)

Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark

3 June 2021

Alexander N. Filippov

Evgeny Burnaev

ArXiv (abs)PDF HTML

Papers citing "Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark"

38 / 38 papers shown

Title
Embedding Empirical Distributions for Computing Optimal Transport Maps Mingchen Jiang Peng Xu Xichen Ye Xiaohui Chen Yun Yang Yifan Chen OT 109 0 0 24 Apr 2025
Gradient Networks Shreyas Chaudhari Srinivasa Pranav J. M. F. Moura 114 0 0 28 Jan 2025
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction Yanshuo Chen Zhengmian Hu Wei Chen Heng Huang OT 94 2 0 01 Nov 2024
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport Milena Gazdieva Jaemoo Choi Alexander Kolesov Jaewoong Choi Petr Mokrov Alexander Korotin OT 142 2 0 04 Oct 2024
Improving Neural Optimal Transport via Displacement Interpolation Jaemoo Choi Yongxin Chen Jaewoong Choi OT 82 2 0 03 Oct 2024
On a Neural Implementation of Brenier's Polar Factorization Nina Vesseron Marco Cuturi 96 2 0 05 Mar 2024
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs Alexander Kolesov Petr Mokrov Igor Udovichenko Milena Gazdieva G. Pammer Anastasis Kratsios Evgeny Burnaev Alexander Korotin OT 89 2 0 02 Oct 2023
Computing high-dimensional optimal transport by flow neural networks Chen Xu Xiuyuan Cheng Yao Xie OT 119 5 0 19 May 2023
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance) Jan Stanczuk Christian Etmann L. Kreusser Carola-Bibiane Schönlieb GAN 62 48 0 02 Mar 2021
Learning High Dimensional Wasserstein Geodesics Shu Liu Shaojun Ma Yongxin Chen H. Zha Haomin Zhou 51 8 0 05 Feb 2021
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization Alexander Korotin Lingxiao Li Justin Solomon Evgeny Burnaev 127 53 0 02 Feb 2021
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks JiaoJiao Fan Amirhossein Taghvaei Yongxin Chen 70 59 0 08 Jul 2020
Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency Guansong Lu Zhiming Zhou Jian Shen Cheng Chen Weinan Zhang Yong Yu OT 41 13 0 14 Mar 2020
Multi-marginal Wasserstein GAN Jingyun Liang Langyuan Mo Yifan Zhang Kui Jia Chunhua Shen Mingkui Tan 55 78 0 03 Nov 2019
How Well Do WGANs Estimate the Wasserstein Metric? Anton Mallasto Guido Montúfar Augusto Gerolin 41 25 0 09 Oct 2019
On the estimation of the Wasserstein distance in generative models Thomas Pinetz Daniel Soukup Thomas Pock GAN 54 9 0 02 Oct 2019
Wasserstein-2 Generative Networks Alexander Korotin Vage Egiazarian Arip Asadulaev Alexander Safin Evgeny Burnaev GAN 196 109 0 28 Sep 2019
Optimal transport mapping via input convex neural networks Ashok Vardhan Makkuva Amirhossein Taghvaei Sewoong Oh Jason D. Lee OT 57 201 0 28 Aug 2019
Adversarial Computation of Optimal Transport Maps Jacob Leygonie Jennifer She Amjad Almahairi Sai Rajeswar Aaron Courville GAN OT 50 21 0 24 Jun 2019
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization Yucheng Chen Matus Telgarsky Chao Zhang Bolton Bailey Daniel J. Hsu Jian-wei Peng GAN OT 43 17 0 08 Jun 2019
On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie Minshuo Chen Haoming Jiang T. Zhao H. Zha OT 64 44 0 01 May 2019
2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs Amirhossein Taghvaei Amin Jalali 63 44 0 19 Feb 2019
(q,p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs Anton Mallasto J. Frellsen Wouter Boomsma Aasa Feragen 44 15 0 10 Feb 2019
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 224 2,150 0 01 Mar 2018
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport Maziar Sanjabi Jimmy Ba Meisam Razaviyayn Jason D. Lee GAN 78 139 0 22 Feb 2018
Wasserstein Divergence for GANs Jiqing Wu Zhiwu Huang Janine Thoma Dinesh Acharya Luc Van Gool 75 139 0 04 Dec 2017
Are GANs Created Equal? A Large-Scale Study Mario Lucic Karol Kurach Marcin Michalski Sylvain Gelly Olivier Bousquet EGVM 80 1,013 0 28 Nov 2017
Large-Scale Optimal Transport and Mapping Estimation Vivien Seguy B. Damodaran Rémi Flamary Nicolas Courty Antoine Rolet Mathieu Blondel OT 68 249 0 07 Nov 2017
The Cramer Distance as a Solution to Biased Wasserstein Gradients Marc G. Bellemare Ivo Danihelka Will Dabney S. Mohamed Balaji Lakshminarayanan Stephan Hoyer Rémi Munos GAN 82 344 0 30 May 2017
Continuously Differentiable Exponential Linear Units Jonathan T. Barron 56 141 0 24 Apr 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 227 9,560 0 31 Mar 2017
Wasserstein GAN Martín Arjovsky Soumith Chintala Léon Bottou GAN 174 4,827 0 26 Jan 2017
DOTmark - A Benchmark for Discrete Optimal Transport Jörn Schrieber Dominic Schuhmacher C. Gottschlich OT 52 41 0 11 Oct 2016
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 280 624 0 22 Sep 2016
Stochastic Optimization for Large-scale Optimal Transport Aude Genevay Marco Cuturi Gabriel Peyré Francis R. Bach OT 77 468 0 27 May 2016
A fixed-point approach to barycenters in Wasserstein space P. C. Álvarez-Esteban E. del Barrio J. A. Cuesta-Albertos Carlos Matrán 52 193 0 17 Nov 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,426 0 28 Nov 2014