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Fréchet Means and Procrustes Analysis in Wasserstein Space

Fréchet Means and Procrustes Analysis in Wasserstein Space

24 January 2017
Y. Zemel
V. Panaretos
ArXivPDFHTML

Papers citing "Fréchet Means and Procrustes Analysis in Wasserstein Space"

18 / 18 papers shown
Title
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
Yiheng Jiang
Sinho Chewi
Aram-Alexandre Pooladian
32
7
0
05 Dec 2023
Non-injectivity of Bures--Wasserstein barycentres in infinite dimensions
Non-injectivity of Bures--Wasserstein barycentres in infinite dimensions
Y. Zemel
24
1
0
15 Nov 2023
Distribution-on-Distribution Regression with Wasserstein Metric:
  Multivariate Gaussian Case
Distribution-on-Distribution Regression with Wasserstein Metric: Multivariate Gaussian Case
Ryotaro Okano
Masaaki Imaizumi
21
2
0
12 Jul 2023
Measure transfer via stochastic slicing and matching
Measure transfer via stochastic slicing and matching
Shiying Li
Caroline Moosmueller
29
3
0
11 Jul 2023
Large Sample Theory for Bures-Wasserstein Barycentres
Large Sample Theory for Bures-Wasserstein Barycentres
Leonardo P. M. Santoro
V. Panaretos
26
3
0
24 May 2023
Errors-in-variables Fréchet Regression with Low-rank Covariate
  Approximation
Errors-in-variables Fréchet Regression with Low-rank Covariate Approximation
Kyunghee Han
Dogyoon Song
22
0
0
16 May 2023
Wasserstein Principal Component Analysis for Circular Measures
Wasserstein Principal Component Analysis for Circular Measures
Mario Beraha
M. Pegoraro
15
2
0
05 Apr 2023
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
Tyler Maunu
Thibaut Le Gouic
Philippe Rigollet
25
5
0
26 Oct 2022
Averaging on the Bures-Wasserstein manifold: dimension-free convergence
  of gradient descent
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent
Jason M. Altschuler
Sinho Chewi
P. Gerber
Austin J. Stromme
18
36
0
16 Jun 2021
Permutation invariant networks to learn Wasserstein metrics
Permutation invariant networks to learn Wasserstein metrics
Arijit Sehanobish
N. Ravindra
David van Dijk
OOD
19
2
0
12 Oct 2020
Multivariate Rank-based Distribution-free Nonparametric Testing using
  Measure Transportation
Multivariate Rank-based Distribution-free Nonparametric Testing using Measure Transportation
Nabarun Deb
B. Sen
45
130
0
18 Sep 2019
Estimation of Wasserstein distances in the Spiked Transport Model
Estimation of Wasserstein distances in the Spiked Transport Model
Jonathan Niles-Weed
Philippe Rigollet
25
102
0
16 Sep 2019
Fast convergence of empirical barycenters in Alexandrov spaces and the
  Wasserstein space
Fast convergence of empirical barycenters in Alexandrov spaces and the Wasserstein space
Thibaut Le Gouic
Q. Paris
Philippe Rigollet
Austin J. Stromme
31
51
0
02 Aug 2019
Statistical data analysis in the Wasserstein space
Statistical data analysis in the Wasserstein space
Jérémie Bigot
27
29
0
19 Jul 2019
Minimax estimation of smooth optimal transport maps
Minimax estimation of smooth optimal transport maps
Jan-Christian Hütter
Philippe Rigollet
OT
29
28
0
14 May 2019
Distilled Wasserstein Learning for Word Embedding and Topic Modeling
Distilled Wasserstein Learning for Word Embedding and Topic Modeling
Hongteng Xu
Wenlin Wang
Wei Liu
Lawrence Carin
MedIm
FedML
32
84
0
12 Sep 2018
Bayesian Learning with Wasserstein Barycenters
Bayesian Learning with Wasserstein Barycenters
Julio D. Backhoff Veraguas
J. Fontbona
Gonzalo Rios
Felipe A. Tobar
20
29
0
28 May 2018
Limit laws of the empirical Wasserstein distance: Gaussian distributions
Limit laws of the empirical Wasserstein distance: Gaussian distributions
Thomas Rippl
Axel Munk
A. Sturm
52
64
0
15 Jul 2015
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