Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation | Paper Citation Record

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This paper cites Barycen- ters in the wasserstein space.SIAM Journal on Mathematical Analysis, 43(2):904–924, 2011.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Barycen- ters in the wasserstein space.SIAM Journal on Mathematical Analysis, 43(2):904–924, 2011

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This paper cites Springer, 2008.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Springer, 2008

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This paper cites A geometric study of wasser- stein spaces: Euclidean spaces.Annali della Scuola Normale Superiore di Pisa-Classe di Scienze, 9(2):297–323, 2010.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A geometric study of wasser- stein spaces: Euclidean spaces.Annali della Scuola Normale Superiore di Pisa-Classe di Scienze, 9(2):297–323, 2010

Reference 3

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This paper cites Model fu- sion via optimal transport.Advances in Neural Information Processing Systems, 33:22045–22055, 2020.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Model fu- sion via optimal transport.Advances in Neural Information Processing Systems, 33:22045–22055, 2020

Reference 4

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This paper cites A barycenter-based approach for the multi-model ensembling of subseasonal forecasts.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A barycenter-based approach for the multi-model ensembling of subseasonal forecasts

Reference 5

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This paper cites Interpolation for robust learning: Data augmen- tation on wasserstein geodesics.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Interpolation for robust learning: Data augmen- tation on wasserstein geodesics

Reference 6

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This paper cites Dataset Distillation via the Wasserstein Metric.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Dataset Distillation via the Wasserstein Metric

Reference 7

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This paper cites Wasser- stein dictionary learning: Optimal transport- based unsupervised nonlinear dictionary learning.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Wasser- stein dictionary learning: Optimal transport- based unsupervised nonlinear dictionary learning

Reference 9

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This paper cites Wasserstein barycenter for multi-source domain adaptation.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Wasserstein barycenter for multi-source domain adaptation

Reference 10

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This paper cites Multi-source domain adaptation through dataset dictionary learning in wasserstein space.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Multi-source domain adaptation through dataset dictionary learning in wasserstein space

Reference 11

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This paper cites Lighter, bet- ter, faster multi-source domain adaptation with gaussian mixture models and optimal transport.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Lighter, bet- ter, faster multi-source domain adaptation with gaussian mixture models and optimal transport

Reference 12

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This paper cites Scalable bayes via barycenter in wasserstein space.Journal of Machine Learning Research, 19(8):1–35, 2018.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Scalable bayes via barycenter in wasserstein space.Journal of Machine Learning Research, 19(8):1–35, 2018

Reference 13

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Observation 8d7baccb-8024-4122-9dfc-d5dd5a01c316 · outbound

This paper cites Fast computa- tion of wasserstein barycenters.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Fast computa- tion of wasserstein barycenters

Reference 14

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This paper cites Iterative bregman projections for regularized transporta- tion problems.SIAM Journal on Scientific Com- puting, 37(2):A1111–A1138, 2015.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Iterative bregman projections for regularized transporta- tion problems.SIAM Journal on Scientific Com- puting, 37(2):A1111–A1138, 2015

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.011289Z

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This paper cites Debiased sinkhorn barycenters.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Debiased sinkhorn barycenters

Reference 16

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This paper cites Gradient descent algo- rithms for bures-wasserstein barycenters.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Gradient descent algo- rithms for bures-wasserstein barycenters

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.324069Z

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This paper cites Statistical inference for bures–wasserstein barycenters.The Annals of Ap- plied Probability, 31(3):1264–1298, 2021.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Statistical inference for bures–wasserstein barycenters.The Annals of Ap- plied Probability, 31(3):1264–1298, 2021

Reference 18

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This paper cites A wasserstein- type distance in the space of gaussian mixture models.SIAM Journal on Imaging Sciences, 13(2):936–970, 2020.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A wasserstein- type distance in the space of gaussian mixture models.SIAM Journal on Imaging Sciences, 13(2):936–970, 2020

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.598756Z

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This paper cites Multi-marginal optimal transport: theory and applications.ESAIM: Mathematical Modelling and Numerical Analysis, 49(6):1771– 1790, 2015.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Multi-marginal optimal transport: theory and applications.ESAIM: Mathematical Modelling and Numerical Analysis, 49(6):1771– 1790, 2015

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.702985Z

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Observation d76886cc-b512-4366-bfa0-e43b1460b907 · outbound

This paper cites Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.818289Z

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Observation ecb61ee1-672f-4305-bd6f-aab938774f02 · outbound

This paper cites Input convex neural networks.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Input convex neural networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.877076Z

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This paper cites Estimating Barycenters of Distributions with Neural Optimal Transport.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Estimating Barycenters of Distributions with Neural Optimal Transport

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:22.929928Z

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Observation c3096705-2b44-464e-8a90-ecd4d18487d5 · outbound

This paper cites Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.012121Z

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Observation 6997cbbc-8d3e-477c-bbd1-d33322fe8b73 · outbound

This paper cites Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.064031Z

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Observation cafaaff1-cbe3-4da2-99cf-07f7a840e41b · outbound

This paper cites Wasserstein itera- tive networks for barycenter estimation.Ad- vances in Neural Information Processing Systems, 35:15672–15686, 2022.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Wasserstein itera- tive networks for barycenter estimation.Ad- vances in Neural Information Processing Systems, 35:15672–15686, 2022

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.115140Z

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Observation db464c2b-2409-41e1-8c66-01dc5889e8d7 · outbound

This paper cites Springer Science & Business Media, 2008.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Springer Science & Business Media, 2008

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.205637Z

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This paper cites an unresolved cited work.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.268443Z

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Observation 0f18b39c-26b7-4bb4-8c9c-f2fc18531c96 · outbound

This paper cites Computa- tional optimal transport: With applications to data science.Foundations and Trends®in Ma- chine Learning, 11(5-6):355–607, 2019.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Computa- tional optimal transport: With applications to data science.Foundations and Trends®in Ma- chine Learning, 11(5-6):355–607, 2019

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.344864Z

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Observation 1268950c-686e-40b5-a6d1-9ed0b140c90e · outbound

This paper cites Re- cent advances in optimal transport for machine learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(2):1161–1180, 2025.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Re- cent advances in optimal transport for machine learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(2):1161–1180, 2025

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.408440Z

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Observation 1b13f113-35f3-4777-a218-91f60c89c129 · outbound

This paper cites M´ emoire sur la th´ eorie des d´ eblais et des remblais.Histoire de l’Acad´ emie Royale des Sciences de Paris, 1781.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation M´ emoire sur la th´ eorie des d´ eblais et des remblais.Histoire de l’Acad´ emie Royale des Sciences de Paris, 1781

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.477015Z

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Observation 317c5e3a-9c92-4b19-97d5-38612061bea9 · outbound

This paper cites On the transfer of masses (in russian).

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation On the transfer of masses (in russian)

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.538866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c75a82a-449f-4e40-9976-ca0efafb0565 · outbound

This paper cites Wasserstein geometry of gaussian measures.Osaka Journal of Mathematics, 2011.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Wasserstein geometry of gaussian measures.Osaka Journal of Mathematics, 2011

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.581083Z

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Observation cc2fd550-be53-403a-bb11-af68665e5b9b · outbound

This paper cites Les ´ el´ ements al´ eatoires de na- ture quelconque dans un espace distanci´ e.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Les ´ el´ ements al´ eatoires de na- ture quelconque dans un espace distanci´ e

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.645697Z

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Observation bc6f1a19-f24a-40a2-82ee-e9132ccbdedb · outbound

This paper cites Riemannian center of mass and mollifier smoothing.Communications on pure and applied mathematics, 30(5):509–541, 1977.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Riemannian center of mass and mollifier smoothing.Communications on pure and applied mathematics, 30(5):509–541, 1977

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.713181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cedb5869-f4ee-4534-8e89-49f5f084b409 · outbound

This paper cites A fixed- point approach to barycenters in wasserstein space.Journal of Mathematical Analysis and Applications, 441(2):744–762, 2016.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A fixed- point approach to barycenters in wasserstein space.Journal of Mathematical Analysis and Applications, 441(2):744–762, 2016

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.774438Z

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Observation b82eb3e9-7ec3-4c36-b0bc-96f19c1ef71d · outbound

This paper cites Optimal transport for multi-source domain adaptation under target shift.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Optimal transport for multi-source domain adaptation under target shift

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.842761Z

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Observation cc25242e-1ba1-4d21-acf3-89eede60ae74 · outbound

This paper cites Springer, 2015.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Springer, 2015

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.908309Z

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Observation 7a7ca110-754a-441c-bb3b-4f2af3e61065 · outbound

This paper cites Dataset dynamics via gradient flows in probability space.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Dataset dynamics via gradient flows in probability space

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.973424Z

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Unavailable: canonical work link unavailable.

Observation a3527581-625d-4fc3-9b51-a145a049fba6 · outbound

This paper cites Gradient methods for solving equations and inequalities.USSR Computational Mathematics and Mathematical Physics, 4(6):17– 32, 1964.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Gradient methods for solving equations and inequalities.USSR Computational Mathematics and Mathematical Physics, 4(6):17– 32, 1964

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.030341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f6b3655-a6bd-44d6-b55d-d03836d688c3 · outbound

This paper cites Linear convergence of gradient and proximal- gradient methods under the polyak- lojasiewicz condition.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Linear convergence of gradient and proximal- gradient methods under the polyak- lojasiewicz condition

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.079195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef7a963f-87cf-420c-9d38-55f545b35135 · outbound

This paper cites Statistical optimal transport.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Statistical optimal transport

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.161457Z

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Unavailable: canonical work link unavailable.

Observation 61030b82-b6c4-43eb-9f92-8e9aa5f53a7f · outbound

This paper cites Differentiable expectation-maximisation and applications to gaussian mixture model optimal transport.arXiv preprint arXiv:2509.02109, 2025.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Differentiable expectation-maximisation and applications to gaussian mixture model optimal transport.arXiv preprint arXiv:2509.02109, 2025

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.242506Z

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Observation 353f0cf8-aa79-443a-a16b-83b36e2fc197 · outbound

This paper cites A review of domain adaptation without target labels.IEEE transactions on pattern analysis and machine in- telligence, 43(3):766–785, 2019.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A review of domain adaptation without target labels.IEEE transactions on pattern analysis and machine in- telligence, 43(3):766–785, 2019

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.310137Z

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Observation 4b760a4d-bb34-4043-bd34-ab2d98333f37 · outbound

This paper cites A survey of multi-source domain adaptation.Infor- mation Fusion, 24:84–92, 2015.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A survey of multi-source domain adaptation.Infor- mation Fusion, 24:84–92, 2015

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.375990Z

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Observation 5e097004-656e-4f21-9b11-ed9cb9d2a2bf · outbound

This paper cites A sur- vey on transfer learning.IEEE Transactions on knowledge and data engineering, 22(10):1345– 1359, 2009.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation A sur- vey on transfer learning.IEEE Transactions on knowledge and data engineering, 22(10):1345– 1359, 2009

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.465073Z

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Unavailable: canonical work link unavailable.

Observation 2e5342e3-7878-4f05-bfb5-3bf0b8a968e1 · outbound

This paper cites Optimal transport for do- main adaptation.IEEE transactions on pattern analysis and machine intelligence, 39(9):1853– 1865, 2016.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Optimal transport for do- main adaptation.IEEE transactions on pattern analysis and machine intelligence, 39(9):1853– 1865, 2016

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.555352Z

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Observation 3686502b-6ecf-41ae-854c-ea2b693f05b0 · outbound

This paper cites Deep residual learning for image recog- nition.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Deep residual learning for image recog- nition

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.708644Z

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Observation c6e451ff-c755-44a7-a9aa-127025eb0260 · outbound

This paper cites Cbramod: A criss-cross brain foun- dation model for eeg decoding.arXiv preprint arXiv:2412.07236, 2024.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Cbramod: A criss-cross brain foun- dation model for eeg decoding.arXiv preprint arXiv:2412.07236, 2024

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.793875Z

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Observation 8cc529e8-88ae-48d7-a6ad-72071a7618a6 · outbound

This paper cites Benchmarking domain adapta- tion for chemical processes on the tennessee east- man process.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Benchmarking domain adapta- tion for chemical processes on the tennessee east- man process

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.856793Z

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Observation ff7c3100-8357-4a9d-a827-0d1073e86476 · outbound

This paper cites Adapting visual category mod- els to new domains.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Adapting visual category mod- els to new domains

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:24.979525Z

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Observation 18d46066-e35e-4a33-83f3-dbeea15e0b77 · outbound

This paper cites Deep hashing network for unsupervised domain adaptation.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Deep hashing network for unsupervised domain adaptation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:25.126817Z

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Observation 298e0cb7-7b38-4ed4-90f9-12cc8ae99679 · outbound

This paper cites Bci competition 2008–graz data set a.Insti- tute for knowledge discovery (laboratory of brain- computer interfaces), Graz University of Technol- ogy, 16(1-6):34, 2008.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Bci competition 2008–graz data set a.Insti- tute for knowledge discovery (laboratory of brain- computer interfaces), Graz University of Technol- ogy, 16(1-6):34, 2008

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:25.254435Z

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Observation 2a5116c1-3fe2-444c-881c-d1b282d0e485 · outbound

This paper cites Automatic sleep staging: A computer assisted approach for optimal combina- tion of features and polysomnographic channels.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Automatic sleep staging: A computer assisted approach for optimal combina- tion of features and polysomnographic channels

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:25.379225Z

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This paper cites PhD thesis, Universit´ e Paris- Saclay, 2024.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation PhD thesis, Universit´ e Paris- Saclay, 2024

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:25.532787Z

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Observation 6b27e9d4-82fa-4f65-aa67-c70cc7ac87f3 · outbound

This paper cites Multi-source do- main adaptation via weighted joint distributions optimal transport.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Multi-source do- main adaptation via weighted joint distributions optimal transport

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:25.731865Z

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This paper cites Vi- sualizing data using t-sne.Journal of machine learning research, 9(Nov):2579–2605, 2008.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Vi- sualizing data using t-sne.Journal of machine learning research, 9(Nov):2579–2605, 2008

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:25.963027Z

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Observation 035e0596-aefa-408f-b017-b63fc7b904bb · outbound

This paper cites Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections.Advances in Neural Information Pro- cessing Systems, 34:29736–29753, 2021.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections.Advances in Neural Information Pro- cessing Systems, 34:29736–29753, 2021

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:26.108130Z

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This paper cites Estimating Barycenters of Measures in High Dimensions.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Estimating Barycenters of Measures in High Dimensions

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:26.206081Z

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Observation c9dfb66f-407e-440d-a725-5b752a96aa44 · outbound

This paper cites Optimal transport mapping via input convex neural networks.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Optimal transport mapping via input convex neural networks

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:26.336434Z

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Observation ba3b3836-3d8c-4c7d-8142-5cd9748a7c3d · outbound

This paper cites Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:26.472042Z

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Observation 9a3d78b9-1580-44f6-9dad-a1197b667363 · outbound

This paper cites Gen- erative adversarial nets.Advances in neural infor- mation processing systems, 27, 2014.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Gen- erative adversarial nets.Advances in neural infor- mation processing systems, 27, 2014

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:26.680376Z

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Observation 544d9c52-7d79-48aa-b2f0-77292a67d670 · outbound

This paper cites Polar factorization and monotone rearrangement of vector-valued functions.Com- munications on pure and applied mathematics, 44(4):375–417, 1991.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Polar factorization and monotone rearrangement of vector-valued functions.Com- munications on pure and applied mathematics, 44(4):375–417, 1991

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:26.873344Z

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This paper cites Kantorovich duality for general transport costs and applications.Journal of Functional Analysis, 273(11):3327–3405, 2017.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Kantorovich duality for general transport costs and applications.Journal of Functional Analysis, 273(11):3327–3405, 2017

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.000154Z

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Observation c8b558dc-7b9f-4045-8b88-b36f17385c90 · outbound

This paper cites Existence, duality, and cycli- cal monotonicity for weak transport costs.Calcu- lus of Variations and Partial Differential Equa- tions, 58(6):203, 2019.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Existence, duality, and cycli- cal monotonicity for weak transport costs.Calcu- lus of Variations and Partial Differential Equa- tions, 58(6):203, 2019

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.113564Z

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Observation 783074bb-9039-457d-a73a-fc95600733a7 · outbound

This paper cites Neural Optimal Transport.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Neural Optimal Transport

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.264503Z

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Observation 5c67eeb3-6014-4da7-9d60-669a5b27ea73 · outbound

This paper cites Optimal entropy-transport problems and a new hellinger–kantorovich distance between positive measures.Inventiones mathematicae, 211(3):969–1117, 2018.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Optimal entropy-transport problems and a new hellinger–kantorovich distance between positive measures.Inventiones mathematicae, 211(3):969–1117, 2018

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.376707Z

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Observation 6b0f7eb7-ea60-42cb-b44f-f5619efbb391 · outbound

This paper cites The ge- ometry of optimal transportation.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation The ge- ometry of optimal transportation

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.491718Z

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This paper cites Normalizing flows: An introduction and review of current methods.IEEE trans- actions on pattern analysis and machine intelli- gence, 43(11):3964–3979, 2020.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Normalizing flows: An introduction and review of current methods.IEEE trans- actions on pattern analysis and machine intelli- gence, 43(11):3964–3979, 2020

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.616452Z

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Observation 7174a21c-1663-4d80-8ade-1ea2aa125d67 · outbound

This paper cites An overview of statistical learning theory.IEEE transactions on neural net- works, 10(5):988–999, 1999.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation An overview of statistical learning theory.IEEE transactions on neural net- works, 10(5):988–999, 1999

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.741383Z

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This paper cites Dataset shift in machine learning.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Dataset shift in machine learning

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:27.924091Z

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Observation 5fc07040-47e5-4663-8203-fe38b136f182 · outbound

This paper cites Multi- source domain adaptation meets dataset distil- lation through dataset dictionary learning.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Multi- source domain adaptation meets dataset distil- lation through dataset dictionary learning

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.092456Z

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This paper cites Sample complexity of optimal transport barycenters with discrete support.arXiv preprint arXiv:2505.21274, 2025.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Sample complexity of optimal transport barycenters with discrete support.arXiv preprint arXiv:2505.21274, 2025

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.263468Z

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Observation 25866f59-fa3d-44b7-bad6-5319fea38731 · outbound

This paper cites Optimal transport for domain adaptation through gaussian mixture models.Transactions on Ma- chine Learning Research, 2025.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Optimal transport for domain adaptation through gaussian mixture models.Transactions on Ma- chine Learning Research, 2025

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.411636Z

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Observation db033d1b-9881-4546-95f8-90a4e57a902e · outbound

This paper cites Adap- tiope: A modern benchmark for unsupervised domain adaptation.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Adap- tiope: A modern benchmark for unsupervised domain adaptation

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.537957Z

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This paper cites An extended tennessee eastman simula- tion dataset for fault-detection and decision sup- port systems.Computers & chemical engineering, 149:107281, 2021.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation An extended tennessee eastman simula- tion dataset for fault-detection and decision sup- port systems.Computers & chemical engineering, 149:107281, 2021

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.631115Z

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This paper cites However, the softmax operation for getting the labels, i.e.,y= softmax(ℓ), is not invertible.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation However, the softmax operation for getting the labels, i.e.,y= softmax(ℓ), is not invertible

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.804364Z

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This paper cites However, applying the softmax breaks the convexity requirement.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation However, applying the softmax breaks the convexity requirement

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:28.946618Z

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This paper cites an unresolved cited work.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Unresolved cited work

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:29.075434Z

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This paper cites These results are available, respectively, in [42] and [73].

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation These results are available, respectively, in [42] and [73]

Reference 80

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This paper cites Our goal here is to perform cross-subjectadaptation, namely, we use data from a given set of source subjects, and try to predict on a target subject.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Our goal here is to perform cross-subjectadaptation, namely, we use data from a given set of source subjects, and try to predict on a target subject

Reference 81

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