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Linearized Wasserstein dimensionality reduction with approximation guarantees

Linearized Wasserstein dimensionality reduction with approximation guarantees

A. Cloninger
Keaton Hamm
Varun Khurana
Caroline Moosmüller
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Papers citing "Linearized Wasserstein dimensionality reduction with approximation guarantees"

11 / 11 papers shown
Title
All You Need is Resistance: On the Equivalence of Effective Resistance and Certain Optimal Transport Problems on Graphs
All You Need is Resistance: On the Equivalence of Effective Resistance and Certain Optimal Transport Problems on Graphs
Sawyer Robertson
Zhengchao Wan
Alexander Cloninger
OT
99
2
0
28 Jan 2025
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems
Nicholas Karris
Evangelos A. Nikitopoulos
Ioannis G. Kevrekidis
Seungjoon Lee
Alexander Cloninger
OT
96
0
0
10 Jan 2025
Manifold learning in Wasserstein space
Manifold learning in Wasserstein space
Keaton Hamm
Caroline Moosmüller
Bernhard Schmitzer
Matthew Thorpe
74
5
0
14 Nov 2023
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning
Keaton Hamm
Nick Henscheid
Shujie Kang
55
18
0
13 Apr 2022
Measure Estimation in the Barycentric Coding Model
Measure Estimation in the Barycentric Coding Model
Matthew Werenski
Ruijie Jiang
Abiy Tasissa
Shuchin Aeron
James M. Murphy
63
14
0
28 Jan 2022
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
Rates of Estimation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
Nabarun Deb
Promit Ghosal
B. Sen
OT
94
73
0
04 Jul 2021
Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations
Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations
Caroline Moosmüller
A. Cloninger
OT
119
44
0
20 Aug 2020
Partitioning signal classes using transport transforms for data analysis and machine learning
Partitioning signal classes using transport transforms for data analysis and machine learning
Akram Aldroubi
Shiying Li
Gustavo K. Rohde
20
19
0
08 Aug 2020
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning
Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning
E. Arias-Castro
Adel Javanmard
Bruno Pelletier
38
22
0
22 Oct 2018
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
Jason M. Altschuler
Jonathan Niles-Weed
Philippe Rigollet
OT
66
592
0
26 May 2017
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
215
4,262
0
04 Jun 2013