Marco Cuturi

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Citations	5918	5494
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i10-index	46	42

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Co-authors

Gabriel PeyréCNRS, DMA, Ecole Normale SupérieureVerified email at ens.fr
Jean-Philippe VertGoogle Brain / Mines ParisTechVerified email at mines-paristech.fr
Aude GenevayMITVerified email at mit.edu
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Nicolas BonneelCNRS / LIRIS / Univ. LyonVerified email at liris.cnrs.fr
Justin SolomonMITVerified email at mit.edu
Alexandre GramfortINRIA, Univ. Paris-SaclayVerified email at inria.fr
Kenji FukumizuThe Institute of Statistical MathematicsVerified email at ism.ac.jp
Arnaud DoucetProfessor of Statistics, University of Oxford & Research Scientist, Google DeepMindVerified email at stats.ox.ac.uk
Fernando de GoesPixar Animation StudiosVerified email at pixar.com
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Tao DuPhD candidate in computer science, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Matthieu HeitzCNRS, Université Lyon 1Verified email at univ-lyon1.fr
David CoeurjollyCNRS, LIRIS UMR 5205, Université de LyonVerified email at liris.cnrs.fr
Olivier TeboulGoogle BrainVerified email at google.com
Vivien SeguyPhD in Machine Learning, Kyoto UniversityVerified email at iip.ist.i.kyoto-u.ac.jp
Hicham JanatiPhd student, Inria SaclayVerified email at inria.fr
Tam LePostdoctoral Researcher at RIKEN AIPVerified email at iip.ist.i.kyoto-u.ac.jp
benamoudirecteur de rechercheVerified email at inria.fr
Luca NennaUniversité Paris-SaclayVerified email at universite-paris-saclay.fr

Marco Cuturi

Google Brain / CREST-ENSAE.

Verified email at google.com - Homepage

machine learning optimal transport


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Sinkhorn Distances: Lightspeed Computation of Optimal Transport M Cuturi Proceedings of the 26th International Conference on Advances in Neural …, 2013	1194	2013
Computational Optimal Transport G Peyré, M Cuturi Foundations and Trends in Machine Learning 11 (5-6), pp. 355-607, 2019	660	2019
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	446	2015
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the International Conference on Machine Learning 2014, JMLR …, 2014	405	2014
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	357	2015
Fast global alignment kernels M Cuturi International Conference in Machine Learning 2011, 2011	265	2011
Learning Generative Models with Sinkhorn Divergences A Genevay, G Peyré, M Cuturi Proceedings of the Twenty-First International Conference on Artifical …, 2017	233*	2017
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	223	2007
Stochastic optimization for large-scale optimal transport A Genevay, M Cuturi, G Peyré, F Bach Advances in neural information processing systems, 3440-3448, 2016	219	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	142	2017
On wasserstein two-sample testing and related families of nonparametric tests A Ramdas, NG Trillos, M Cuturi Entropy 19 (2), 47, 2017	115	2017
A smoothed dual approach for variational wasserstein problems M Cuturi, G Peyré SIAM J. Imaging Sciences 9 (1), 320–343, 2016	115	2016
Semigroup kernels on measures M Cuturi, K Fukumizu, JP Vert Journal of Machine Learning Research 6 (Jul), 1169-1198, 2005	100	2005
Sliced wasserstein kernel for persistence diagrams M Carriere, M Cuturi, S Oudot arXiv preprint arXiv:1706.03358, 2017	98	2017
Gromov-wasserstein averaging of kernel and distance matrices G Peyré, M Cuturi, J Solomon International Conference on Machine Learning, 2664-2672, 2016	95	2016
Fast dictionary learning with a smoothed Wasserstein loss A Rolet, M Cuturi, G Peyré Artificial Intelligence and Statistics, 630-638, 2016	94	2016
Wasserstein training of restricted Boltzmann machines G Montavon, KR Müller, M Cuturi Advances in Neural Information Processing Systems 29, 3718-3726, 2016	90*	2016
Wasserstein Barycentric Coordinates: Histogram Regression Using Optimal Transport N Bonneel, G Peyré, M Cuturi ACM Transactions on Graphics 35 (4), 2016	82	2016
Ground Metric Learning M Cuturi, D Avis Journal of Machine Learning Research 15 (February), 533−564, 2014	76	2014
Sample complexity of sinkhorn divergences A Genevay, L Chizat, F Bach, M Cuturi, G Peyré The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	75	2019

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