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The sliced Wasserstein (SW) distance has been widely recognized as a statistically effective and computationally efficient metric between two probability measures.
The minimum distance method
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Unidimensional and evolution methods for optimal transportation
N. Bonnotte · 2013
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Sinkhorn distances: Lightspeed computation of optimal transport
M. Cuturi · 2013
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A probabilistic theory of pattern recognition
L. Devroye, L. Györfi, and G. Lugosi · 2013
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Sliced and Radon Wasserstein barycenters of measures
N. Bonneel, J. Rabin, G. Peyré, and H. Pfister · 2015
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Shapenet: An information-rich 3d model repository
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Deep learning face attributes in the wild
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Optimal transport for applied mathematicians
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3d shapenets: A deep representation for volumetric shapes
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Improved techniques for training GANs
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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Hyperspherical variational auto-encoders
T. R. Davidson, L. Falorsi, N. De Cao, T. Kipf, and J. M. Tomczak · 2018
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Generative modeling using the sliced Wasserstein distance
I. Deshpande, Z. Zhang, and A. G. Schwing · 2018
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Sliced Wasserstein distance for learning Gaussian mixture models
S. Kolouri, G. K. Rohde, and H. Hoffmann · 2018
Sliced score matching: A scalable approach to density and score estimation
Y. Song, S. Garg, J. Shi, and S. Ermon · 2020
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Pot: Python optimal transport
R. Flamary, N. Courty, A. Gramfort, M. Z. Alaya, A. Boisbunon, S. Chambon, L. Chapel, A. Corenflos, K. Fatras, N. Fournier, L. Gautheron, N. T. Gayraud, H. Janati, A. Rakotomamonjy, I. Redko, A. Rolet, A. Schutz, V. Seguy, D. J. Sutherland, R. Tavenard, A. Tong, and T. Vayer · 2021
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Sliced mutual information: A scalable measure of statistical dependence
Z. Goldfeld and K. Greenewald · 2021
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Distributional sliced-Wasserstein and applications to generative modeling
K. Nguyen, N. Ho, T. Pham, and H. Bui · 2021
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Improving relational regularized autoencoders with spherical sliced fused Gromov-Wasserstein
K. Nguyen, S. Nguyen, N. Ho, T. Pham, and H. Bui · 2021
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Cited alongside, same era.
Max-sliced Wasserstein distance and its use for GANs
I. Deshpande, Y.-T. Hu, R. Sun, A. Pyrros, N. Siddiqui, S. Koyejo, Z. Zhao, D. Forsyth, and A. G. Schwing · 2019
Cited alongside, same era.
Interpolating between optimal transport and MMD using Sinkhorn divergences
J. Feydy, T. Séjourné, F.-X. Vialard, S.-i. Amari, A. Trouve, and G. Peyré · 2019
Cited alongside, same era.
Generalized sliced Wasserstein distances
S. Kolouri, K. Nadjahi, U. Simsekli, R. Badeau, and G. Rohde · 2019
Cited alongside, same era.
Sliced Wasserstein discrepancy for unsupervised domain adaptation
C.-Y. Lee, T. Batra, M. H. Baig, and D. Ulbricht · 2019
Cited alongside, same era.
Sliced-Wasserstein flows: Nonparametric generative modeling via optimal transport and diffusions
A. Liutkus, U. Simsekli, S. Majewski, A. Durmus, and F.-R. Stöter · 2019
Cited alongside, same era.
Orthogonal estimation of Wasserstein distances
M. Rowland, J. Hron, Y. Tang, K. Choromanski, T. Sarlos, and A. Weller · 2019
Cited alongside, same era.
T. Nguyen, Q.-H. Pham, T. Le, T. Pham, N. Ho, and B.-S. Hua · 2021
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Sliced Wasserstein variational inference
M. Yi and S. Liu · 2021
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Efficient gradient flows in sliced-Wasserstein space
C. Bonet, N. Courty, F. Septier, and L. Drumetz · 2022
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Amortized projection optimization for sliced Wasserstein generative models
K. Nguyen and N. Ho · 2022
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Statistical, robustness, and computational guarantees for sliced wasserstein distances
S. Nietert, R. Sadhu, Z. Goldfeld, and K. Kato · 2022
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Lidar upsampling with sliced Wasserstein distance
A. Savkin, Y. Wang, S. Wirkert, N. Navab, and F. Tombari · 2022
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Probabilistic Machine Learning: Advanced Topics
K. P. Murphy · 2023
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Control variate sliced wasserstein estimators
K. Nguyen and N. Ho · 2023
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Self-attention amortized distributional projection optimization for sliced Wasserstein point-cloud reconstruction
K. Nguyen, D. Nguyen, and N. Ho · 2023
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Shedding a pac-bayesian light on adaptive sliced-wasserstein distances
R. Ohana, K. Nadjahi, A. Rakotomamonjy, and L. Ralaivola · 2023
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