Wasserstein-2 Generative Networks

28 September 2019

Papers citing "Wasserstein-2 Generative Networks"

24 / 24 papers shown

Title
Non-geodesically-convex optimization in the Wasserstein space Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Petrus Mikkola Marcelo Hartmann Kai Puolamaki Arto Klami 53 2 0 08 Jan 2025
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport Milena Gazdieva Jaemoo Choi Alexander Kolesov Jaewoong Choi Petr Mokrov Alexander Korotin OT 44 0 0 04 Oct 2024
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights Zeqin Yang Weilin Chen Ruichu Cai Yuguang Yan Zhifeng Hao Zhipeng Yu Zhichao Zou Zhen Peng Zhen Peng Jiecheng Guo 54 3 0 27 Jun 2024
On a Neural Implementation of Brenier's Polar Factorization Nina Vesseron Marco Cuturi 39 2 0 05 Mar 2024
Light Schrödinger Bridge Alexander Korotin Nikita Gushchin Evgeny Burnaev OT 26 4 0 02 Oct 2023
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 34 2 0 02 Oct 2023
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport Jaemoo Choi Jaewoong Choi Myung-joo Kang OT 23 19 0 24 May 2023
Computing high-dimensional optimal transport by flow neural networks Chen Xu Xiuyuan Cheng Yao Xie OT 35 4 0 19 May 2023
Keypoint-Guided Optimal Transport Xiang Gu Yucheng Yang Weizhen Zeng Jian-jun Sun Zongben Xu 26 1 0 23 Mar 2023
The Monge Gap: A Regularizer to Learn All Transport Maps Théo Uscidda Marco Cuturi OT 47 26 0 09 Feb 2023
Stochastic optimal transport in Banach Spaces for regularized estimation of multivariate quantiles Bernard Bercu Jérémie Bigot Gauthier Thurin 28 2 0 02 Feb 2023
Extremal Domain Translation with Neural Optimal Transport Milena Gazdieva Alexander Korotin Daniil Selikhanovych Evgeny Burnaev OT 20 11 0 30 Jan 2023
Entropic Neural Optimal Transport via Diffusion Processes Nikita Gushchin Alexander Kolesov Alexander Korotin Dmitry Vetrov Evgeny Burnaev OT DiffM 35 36 0 02 Nov 2022
A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applications Tristan Milne Étienne Bilocq A. Nachman OT 17 3 0 02 Nov 2022
Towards Explaining Distribution Shifts Sean Kulinski David I. Inouye OffRL FAtt 35 23 0 19 Oct 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Wasserstein Iterative Networks for Barycenter Estimation Alexander Korotin Vage Egiazarian Lingxiao Li Evgeny Burnaev 24 24 0 28 Jan 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 72 54 0 04 Dec 2021
Input Convex Gradient Networks Jack Richter-Powell Jonathan Lorraine Brandon Amos 10 15 0 23 Nov 2021
Efficient Gradient Flows in Sliced-Wasserstein Space Clément Bonet Nicolas Courty Franccois Septier Lucas Drumetz 29 21 0 21 Oct 2021
Generative Modeling with Optimal Transport Maps Litu Rout Alexander Korotin Evgeny Burnaev OT DiffM 122 65 0 06 Oct 2021
Riemannian Convex Potential Maps Samuel N. Cohen Brandon Amos Y. Lipman 18 22 0 18 Jun 2021
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 112 95 0 10 Dec 2020
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 175 597 0 22 Sep 2016