Marco Cuturi
Marco Cuturi
Google Brain / CREST-ENSAE.
Verified email at google.com - Homepage
TitleCited byYear
Sinkhorn Distances: Lightspeed Computation of Optimal Transport
M Cuturi
Advances in Neural Information Processing Systems, 2292-2300, 2013
7422013
Iterative Bregman projections for regularized transportation problems
JD Benamou, G Carlier, M Cuturi, L Nenna, G Peyré
SIAM Journal on Scientific Computing 37 (2), A1111-A1138, 2015
3272015
Fast computation of wasserstein barycenters
M Cuturi, A Doucet
Proceedings of the International Conference on Machine Learning 2014, JMLR …, 2014
2842014
Computational Optimal Transport
G Peyré, M Cuturi
Foundations and Trends in Machine Learning 11 (5-6), pp. 355-607, 2019
2782019
Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains
J Solomon, F de Goes, G Peyré, M Cuturi, A Butscher, A Nguyen, T Du, ...
ACM Transactions on Graphics (TOG) SIGGRAPH, 2015, 2015
2572015
Fast global alignment kernels
M Cuturi
International Conference in Machine Learning 2011, 2011
2212011
A kernel for time series based on global alignments
M Cuturi, JP Vert, O Birkenes, T Matsui
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE …, 2007
2022007
Stochastic optimization for large-scale optimal transport
A Genevay, M Cuturi, G Peyré, F Bach
Advances in neural information processing systems, 3440-3448, 2016
1412016
Learning Generative Models with Sinkhorn Divergences
A Genevay, G Peyré, M Cuturi
Proceedings of the Twenty-First International Conference on Artifical …, 2017
1092017
Semigroup kernels on measures
M Cuturi, K Fukumizu, JP Vert
Journal of Machine Learning Research 6 (Jul), 1169-1198, 2005
1022005
A smoothed dual approach for variational wasserstein problems
M Cuturi, G Peyré
SIAM J. Imaging Sciences 9 (1), 320–343, 2016
872016
Fast dictionary learning with a smoothed Wasserstein loss
A Rolet, M Cuturi, G Peyré
Artificial Intelligence and Statistics, 630-638, 2016
732016
Wasserstein training of restricted Boltzmann machines
G Montavon, KR Müller, M Cuturi
Advances in Neural Information Processing Systems, 3718-3726, 2016
69*2016
Soft-DTW: a differentiable loss function for time-series
M Cuturi, M Blondel
Proceedings of the 34th International Conference on Machine Learning, PMLR …, 2017
642017
Ground Metric Learning
M Cuturi, D Avis
Journal of Machine Learning Research 15 (February), 533−564, 2014
632014
Sliced wasserstein kernel for persistence diagrams
M Carriere, M Cuturi, S Oudot
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
592017
On wasserstein two-sample testing and related families of nonparametric tests
A Ramdas, N Trillos, M Cuturi
Entropy 19 (2), 47, 2017
562017
Principal geodesic analysis for probability measures under the optimal transport metric
V Seguy, M Cuturi
Advances in Neural Information Processing Systems, 3312-3320, 2015
552015
The context-tree kernel for strings
M Cuturi, JP Vert
Neural Networks 18 (8), 1111-1123, 2005
552005
Wasserstein Barycentric Coordinates: Histogram Regression Using Optimal Transport
N Bonneel, G Peyré, M Cuturi
ACM Transactions on Graphics 35 (4), 2016
502016
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Articles 1–20