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2106.01954
Cited By
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
3 June 2021
Alexander Korotin
Lingxiao Li
Aude Genevay
Justin Solomon
Alexander N. Filippov
Evgeny Burnaev
OT
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Papers citing
"Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark"
25 / 25 papers shown
Title
Gradient Networks
Shreyas Chaudhari
Srinivasa Pranav
J. M. F. Moura
50
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
47
1
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
44
0
0
04 Oct 2024
Improving Neural Optimal Transport via Displacement Interpolation
Jaemoo Choi
Yongxin Chen
Jaewoong Choi
OT
43
0
0
03 Oct 2024
On a Neural Implementation of Brenier's Polar Factorization
Nina Vesseron
Marco Cuturi
41
2
0
05 Mar 2024
A Computational Framework for Solving Wasserstein Lagrangian Flows
Kirill Neklyudov
Rob Brekelmans
Alexander Tong
Lazar Atanackovic
Qiang Liu
Alireza Makhzani
OT
31
17
0
16 Oct 2023
Light Schrödinger Bridge
Alexander Korotin
Nikita Gushchin
Evgeny Burnaev
OT
29
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
37
2
0
02 Oct 2023
Fitted Value Iteration Methods for Bicausal Optimal Transport
Erhan Bayraktar
Bingyan Han
OT
6
6
0
22 Jun 2023
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Tung Le
Khai Nguyen
Shanlin Sun
Kun Han
Nhat Ho
Xiaohui Xie
27
5
0
27 May 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
Semi-supervised Learning of Pushforwards For Domain Translation & Adaptation
N. Panda
Natalie Klein
Dominic Yang
P. Gasda
Diane Oyen
27
1
0
18 Apr 2023
The Monge Gap: A Regularizer to Learn All Transport Maps
Théo Uscidda
Marco Cuturi
OT
50
26
0
09 Feb 2023
Extremal Domain Translation with Neural Optimal Transport
Milena Gazdieva
Alexander Korotin
Daniil Selikhanovych
Evgeny Burnaev
OT
23
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
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows
G. Morel
Lucas Drumetz
Simon Benaïchouche
Nicolas Courty
F. Rousseau
OT
28
6
0
22 Sep 2022
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Xingchao Liu
Chengyue Gong
Qiang Liu
OOD
35
842
0
07 Sep 2022
Fast Nonlinear Vector Quantile Regression
Aviv A. Rosenberg
S. Vedula
Yaniv Romano
A. Bronstein
18
7
0
30 May 2022
Wasserstein Iterative Networks for Barycenter Estimation
Alexander Korotin
Vage Egiazarian
Lingxiao Li
Evgeny Burnaev
24
24
0
28 Jan 2022
Variational Wasserstein Barycenters with c-Cyclical Monotonicity
Jinjin Chi
Zhiyao Yang
Jihong Ouyang
Ximing Li
24
5
0
22 Oct 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
Wasserstein-2 Generative Networks
Alexander Korotin
Vage Egiazarian
Arip Asadulaev
Alexander Safin
E. Burnaev
GAN
125
100
0
28 Sep 2019
Input Convex Neural Networks
Brandon Amos
Lei Xu
J. Zico Kolter
175
598
0
22 Sep 2016
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