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Entropy regularization in optimal transport (OT) has been the driver of many recent interests for Wasserstein metrics and barycenters in machine learning.
Harmonic Analysis on Semigroups
Berg, C., Christensen, J. P. R., and Ressel, P · 1984
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Real-time computerized annotation of pictures
Li, J. and Wang, J. Z · 2006
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MNIST handwritten digit database
LeCun, Y. and Cortes, C · 2010
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Barycenters in the Wasserstein space
Agueh, M. and Carlier, G · 2011
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Scikit-learn: Machine learning in Python
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E · 2011
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Sinkhorn Distances: Lightspeed Computation of Optimal Transport
Cuturi, M · 2013
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Iterative bregman projections for regularized transportation problems
Benamou, J.-D., Carlier, G., Cuturi, M., Nenna, L., and Peyré, G · 2014
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Fast computation of wasserstein barycenters
Cuturi, M. and Doucet, A · 2014
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A symmetry preserving algorithm for matrix scaling
Knight, P. A., Ruiz, D., and Uçar, B · 2014
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Convolutional Wasserstein distances: Efficient optimal transportation on geometric domains
Solomon, J., de Goes, F., Peyré, G., Cuturi, M., Butscher, A., Nguyen, A., Du, T., and Guibas, L · 2015
Earlier work this paper cites.
Wasserstein barycentric coordinates: Histogram regression using optimal transport
Bonneel, N., Peyré, G., and Cuturi, M · 2016
Cited alongside, same era.
Stabilized sparse scaling algorithms for entropy regularized transport problems
Schmitzer, B · 2016
Cited alongside, same era.
Scaling Algorithms for Unbalanced Transport Problems
Chizat, L., Peyré, G., Schmitzer, B., and Vialard, F.-X · 2017
Cited alongside, same era.
About the analogy between optimal transport and minimal entropy
Ivan Gentil, Christian Léonard, L. R · 2017
Cited alongside, same era.
Automatic differentiation in pytorch
Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A · 2017
Cited alongside, same era.
On wasserstein two-sample testing and related families of nonparametric tests
Differential properties of sinkhorn approximation for learning with wasserstein distance
Luise, G., Rudi, A., Pontil, M., and Ciliberto, C · 2018
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Computational Optimal Transport
Peyré, G. and Cuturi, M · 2018
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Entropic optimal transport is maximum-likelihood deconvolution
Rigollet, P. and Weed, J · 2018
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Information geometry for regularized optimal transport and barycenters of patterns
Amari, S.-i., Karakida, R., Oizumi, M., and Cuturi, M · 2019
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An Optimal Transport approach for the Schrodinger bridge problem and convergence of Sinkhorn algorithm, 2019
Di Marino, S. and Gerolin, A · 2019
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Interior-point methods strike back: Solving the wasserstein barycenter problem
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Ramdas, A., Trillos, N., and Cuturi, M · 2017
Cited alongside, same era.
Smooth and sparse optimal transport
Blondel, M., Seguy, V., and Rolet, A · 2018
Cited alongside, same era.
Interpolating between optimal transport and mmd using sinkhorn divergences
Feydy, J., Séjourné, T., Vialard, F.-X., Amari, S.-i., Trouvé, A., and Peyré, G · 2018
Cited alongside, same era.
Learning generative models with sinkhorn divergences
Genevay, A., Peyré, G., and Cuturi, M · 2018
Cited alongside, same era.
Ge, D., Wang, H., Xiong, Z., and Ye, Y · 2019
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Sinkhorn barycenters with free support via frank-wolfe algorithm
Luise, G., Salzo, S., Pontil, M., and Ciliberto, C · 2019
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Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
Mena, G. and Weed, J · 2019
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Sullivan, C. and Kaszynski, A · 2019
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