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The Wasserstein distance and its variations, e.g., the sliced-Wasserstein (SW) distance, have recently drawn attention from the machine learning community.
Uber die bestimmug von funktionen durch ihre integralwerte laengs geweisser mannigfaltigkeiten
Radon, J · 1917
Earlier work this paper cites.
Differential forms and integral geometry
Gel’fand, I. M., Graev, M. I., and Shapiro, Z. Y · 1969
Earlier work this paper cites.
The inversion problem and applications of the generalized Radon transform
Beylkin, G · 1984
Earlier work this paper cites.
The mathematics of computerized tomography , volume 32
Natterer, F · 1986
Earlier work this paper cites.
Polar factorization and monotone rearrangement of vector-valued functions
Brenier, Y · 1991
Earlier work this paper cites.
Inversion of the generalized Radon transform
Denisyuk, A · 1994
Earlier work this paper cites.
Gradient-based learning applied to document recognition
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P · 1998
Earlier work this paper cites.
The universality of the Radon transform
Ehrenpreis, L · 2003
Earlier work this paper cites.
Inside out: inverse problems and applications , volume 47
Uhlmann, G · 2003
Earlier work this paper cites.
Generalized transforms of Radon type and their applications
Kuchment, P · 2006
Earlier work this paper cites.
Optimal transport: old and new , volume 338
Villani, C · 2008
Earlier work this paper cites.
The Radon transform on Rn
Helgason, S · 2011
Earlier work this paper cites.
Penalized Fisher discriminant analysis and its application to image-based morphometry
Wang, W., Mo, Y., Ozolek, J. A., and Rohde, G. K · 2011
Earlier work this paper cites.
Unidimensional and evolution methods for optimal transportation
Bonnotte, N · 2013
Earlier work this paper cites.
Sinkhorn distances: Lightspeed computation of optimal transport
Cuturi, M · 2013
Earlier work this paper cites.
Wang, W., Slepčev, D., Basu, S., Ozolek, J. A., and Rohde, G. K · 2013
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
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Wasserstein propagation for semi-supervised learning
Solomon, J., Rustamov, R., Guibas, L., and Butscher, A · 2014
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Sliced and Radon Wasserstein barycenters of measures
Bonneel, N., Rabin, J., Peyré, G., and Pfister, H · 2015
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A smoothed dual approach for variational Wasserstein problems
Cuturi, M. and Peyré, G · 2015
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Learning with a Wasserstein loss
Sliced Wasserstein kernel for persistence diagrams
Carriere, M., Cuturi, M., and Oudot, S · 2017
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Optimal transport for domain adaptation
Courty, N., Flamary, R., Tuia, D., and Rakotomamonjy, A · 2017
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Improved training of Wasserstein GANs
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
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Injectivity and stability for a generic class of generalized Radon transforms
Homan, A. and Zhou, H · 2017
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Progressive growing of GANs for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2017
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Optimal mass transport: Signal processing and machine-learning applications
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Frogner, C., Zhang, C., Mobahi, H., Araya, M., and Poggio, T. A · 2015
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Lévy, B · 2015
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Oberman, A. M. and Ruan, Y · 2015
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Rouviere, F · 2015
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Solomon, J., De Goes, F., Peyré, G., Cuturi, M., Butscher, A., Nguyen, A., Du, T., and Guibas, L · 2015
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Kitagawa, J., Mérigot, Q., and Thibert, B · 2016
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Montavon, G., Müller, K.-R., and Cuturi, M · 2016
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Kolouri, S., Park, S. R., Thorpe, M., Slepcev, D., and Rohde, G. K · 2017
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Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A · 2017
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Generative modeling using the sliced Wasserstein distance
Deshpande, I., Zhang, Z., and Schwing, A · 2018
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Sliced Wasserstein distance for learning gaussian mixture models
Kolouri, S., Rohde, G. K., and Hoffmann, H · 2018
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Peyré, G. and Cuturi, M · 2018
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Wasserstein dictionary learning: Optimal transport-based unsupervised nonlinear dictionary learning
Schmitz, M. A., Heitz, M., Bonneel, N., Ngole, F., Coeurjolly, D., Cuturi, M., Peyré, G., and Starck, J.-L · 2018
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Şimşekli, U., Liutkus, A., Majewski, S., and Durmus, A · 2018
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Tolstikhin, I., Bousquet, O., Gelly, S., and Schoelkopf, B · 2018
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Sliced Wasserstein auto-encoders
Kolouri, S., Pope, P. E., Martin, C. E., and Rohde, G. K · 2019
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