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2001.01700
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Gradient descent algorithms for Bures-Wasserstein barycenters
Annual Conference Computational Learning Theory (COLT), 2020
6 January 2020
Sinho Chewi
Tyler Maunu
Philippe Rigollet
Austin J. Stromme
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Papers citing
"Gradient descent algorithms for Bures-Wasserstein barycenters"
50 / 54 papers shown
Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation
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Exact Solutions to the Quantum Schrödinger Bridge Problem
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Convergence Analysis of the Wasserstein Proximal Algorithm beyond Geodesic Convexity
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Xiaohui Chen
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Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Matthew Werenski
Brendan Mallery
Shuchin Aeron
James M. Murphy
399
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31 Oct 2024
On Barycenter Computation: Semi-Unbalanced Optimal Transport-based Method on Gaussians
Ngoc-Hai Nguyen
Dung D. Le
Hoang Nguyen
Tung Pham
Nhat Ho
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355
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10 Oct 2024
How should we aggregate ratings? Accounting for personal rating scales via Wasserstein barycenters
Daniel Raban
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01 Oct 2024
Large Deviations Principle for Bures-Wasserstein Barycenters
Adam Quinn Jaffe
Leonardo P. M. Santoro
357
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17 Sep 2024
Disciplined Geodesically Convex Programming
Andrew Cheng
Vaibhav Dixit
Melanie Weber
384
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07 Jul 2024
Wasserstein gradient flow for optimal probability measure decomposition
Jiangze Han
Chris Ryan
Xin T. Tong
277
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03 Jun 2024
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space
Annual Conference Computational Learning Theory (COLT), 2023
Yiheng Jiang
Sinho Chewi
Aram-Alexandre Pooladian
689
18
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05 Dec 2023
Duality of Bures and Shape Distances with Implications for Comparing Neural Representations
Sarah E. Harvey
Brett W. Larsen
Alex H. Williams
312
20
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19 Nov 2023
Non-injectivity of Bures--Wasserstein barycentres in infinite dimensions
Y. Zemel
266
2
0
15 Nov 2023
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
International Conference on Learning Representations (ICLR), 2023
Zhaoyuan Yang
Zhengyang Yu
Zhiwei Xu
Jaskirat Singh
Jing Zhang
Dylan Campbell
Peter Tu
Richard Hartley
379
23
0
12 Nov 2023
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Rentian Yao
Linjun Huang
Yun Yang
322
7
0
01 Nov 2023
Measure transfer via stochastic slicing and matching
Shiying Li
Caroline Moosmueller
Yongzhe Wang
292
5
0
11 Jul 2023
Last-Iterate Convergence of Adaptive Riemannian Gradient Descent for Equilibrium Computation
Yong Cai
Michael I. Jordan
Tianyi Lin
Argyris Oikonomou
Emmanouil-Vasileios Vlatakis-Gkaragkounis
356
5
0
29 Jun 2023
Transportation of Measure Regression in Higher Dimensions
Laya Ghodrati
V. Panaretos
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386
4
0
27 May 2023
Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Abdelwahed Khamis
Russell Tsuchida
Mohamed Tarek
V. Rolland
Lars Petersson
OT
510
34
0
08 May 2023
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space
International Conference on Machine Learning (ICML), 2023
Michael Diao
Krishnakumar Balasubramanian
Sinho Chewi
Adil Salim
BDL
181
45
0
10 Apr 2023
Doubly Regularized Entropic Wasserstein Barycenters
Lénaïc Chizat
353
16
0
21 Mar 2023
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss
International Conference on Machine Learning (ICML), 2023
Pierre Bréchet
Katerina Papagiannouli
Jing An
Guido Montúfar
425
7
0
06 Mar 2023
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow
Yuling Yan
Kaizheng Wang
Philippe Rigollet
363
34
0
04 Jan 2023
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Tyler Maunu
Thibaut Le Gouic
Philippe Rigollet
215
9
0
26 Oct 2022
Rieoptax: Riemannian Optimization in JAX
Saiteja Utpala
Andi Han
Pratik Jawanpuria
Bamdev Mishra
255
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10 Oct 2022
Quantitative Stability of Barycenters in the Wasserstein Space
Probability theory and related fields (PTRF), 2022
G. Carlier
Alex Delalande
Q. Mérigot
281
17
0
21 Sep 2022
Variational inference via Wasserstein gradient flows
Neural Information Processing Systems (NeurIPS), 2022
Marc Lambert
Sinho Chewi
Francis R. Bach
Silvère Bonnabel
Philippe Rigollet
BDL
DRL
381
99
0
31 May 2022
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters
Tim Tsz-Kit Lau
Han Liu
OOD
379
3
0
23 Mar 2022
An entropic generalization of Caffarelli's contraction theorem via covariance inequalities
Comptes rendus. Mathematique (C. R. Math.), 2022
Sinho Chewi
Aram-Alexandre Pooladian
220
49
0
09 Mar 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization
International Conference on Machine Learning (ICML), 2022
Wei Jiang
Bokun Wang
Yibo Wang
Lijun Zhang
Tianbao Yang
516
23
0
15 Feb 2022
The Schrödinger Bridge between Gaussian Measures has a Closed Form
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Charlotte Bunne
Ya-Ping Hsieh
Marco Cuturi
Andreas Krause
OT
457
75
0
11 Feb 2022
Wasserstein Iterative Networks for Barycenter Estimation
Neural Information Processing Systems (NeurIPS), 2022
Alexander Korotin
Vage Egiazarian
Lingxiao Li
Evgeny Burnaev
430
34
0
28 Jan 2022
Measure Estimation in the Barycentric Coding Model
International Conference on Machine Learning (ICML), 2022
Matthew Werenski
Ruijie Jiang
Abiy Tasissa
Shuchin Aeron
James M. Murphy
302
16
0
28 Jan 2022
Dimensionality Reduction for Wasserstein Barycenter
Zachary Izzo
Sandeep Silwal
Samson Zhou
349
21
0
18 Oct 2021
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
Nabarun Deb
Promit Ghosal
B. Sen
OT
374
87
0
04 Jul 2021
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent
Jason M. Altschuler
Sinho Chewi
P. Gerber
Austin J. Stromme
414
53
0
16 Jun 2021
Frank-Wolfe Methods in Probability Space
Carson Kent
Jose H. Blanchet
Peter Glynn
173
9
0
11 May 2021
Sampling From the Wasserstein Barycenter
Chiheb Daaloul
Thibaut Le Gouic
J. Liandrat
M. I. O. Technology
217
6
0
04 May 2021
Online learning with exponential weights in metric spaces
Q. Paris
425
4
0
26 Mar 2021
A novel notion of barycenter for probability distributions based on optimal weak mass transport
Neural Information Processing Systems (NeurIPS), 2021
Elsa Cazelles
Felipe A. Tobar
J. Fontbona
OT
316
14
0
26 Feb 2021
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
International Conference on Learning Representations (ICLR), 2021
Alexander Korotin
Lingxiao Li
Justin Solomon
Evgeny Burnaev
382
58
0
02 Feb 2021
Wasserstein barycenters are NP-hard to compute
SIAM Journal on Mathematics of Data Science (SIMODS), 2021
Jason M. Altschuler
Enric Boix-Adserà
OT
712
58
0
04 Jan 2021
Randomised Wasserstein Barycenter Computation: Resampling with Statistical Guarantees
F. Heinemann
Axel Munk
Y. Zemel
259
19
0
11 Dec 2020
Fast and Smooth Interpolation on Wasserstein Space
Sinho Chewi
Julien Clancy
Thibaut Le Gouic
Philippe Rigollet
George Stepaniants
Austin J. Stromme
253
32
0
22 Oct 2020
Sinkhorn Barycenter via Functional Gradient Descent
Zebang Shen
Zhenfu Wang
Alejandro Ribeiro
Hamed Hassani
251
10
0
20 Jul 2020
Estimating Barycenters of Measures in High Dimensions
Samuel N. Cohen
Michael Arbel
M. Deisenroth
393
27
0
14 Jul 2020
Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
International Conference on Machine Learning (ICML), 2020
JiaoJiao Fan
Amirhossein Taghvaei
Yongxin Chen
466
65
0
08 Jul 2020
Stochastic Saddle-Point Optimization for Wasserstein Barycenters
Optimization Letters (Optim. Lett.), 2020
D. Tiapkin
Alexander Gasnikov
Pavel Dvurechensky
240
8
0
11 Jun 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence
Neural Information Processing Systems (NeurIPS), 2020
Sinho Chewi
Thibaut Le Gouic
Chen Lu
Tyler Maunu
Philippe Rigollet
401
80
0
03 Jun 2020
Projection to Fairness in Statistical Learning
Thibaut Le Gouic
Jean-Michel Loubes
Philippe Rigollet
276
3
0
24 May 2020
Exponential ergodicity of mirror-Langevin diffusions
Sinho Chewi
Thibaut Le Gouic
Chen Lu
Tyler Maunu
Philippe Rigollet
Austin J. Stromme
254
54
0
19 May 2020
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