Marco Cuturi - Google Scholar Citations

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Gabriel PeyréCNRS, DMA, Ecole Normale SupérieureVerified email at ens.fr
Jean-Philippe VertGoogle Brain / Mines ParisTechVerified email at mines-paristech.fr
Genevay AudeMITVerified email at mit.edu
Nicolas BonneelCNRS / LIRIS / Univ. LyonVerified email at liris.cnrs.fr
Justin SolomonMITVerified email at mit.edu
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
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Fernando de GoesPixar Animation StudiosVerified email at pixar.com
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Tao DuPhD student, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Alexandre GramfortINRIA, Univ. Paris-SaclayVerified email at inria.fr
Vivien SeguyPhD in Machine Learning, Kyoto UniversityVerified email at iip.ist.i.kyoto-u.ac.jp
Matthieu HeitzCNRS, Université Lyon 1Verified email at univ-lyon1.fr
David CoeurjollyCNRS, LIRIS UMR 5205, Université de LyonVerified email at liris.cnrs.fr
benamoudirecteur de rechercheVerified email at inria.fr
Luca NennaUniversité Paris SudVerified email at math.u-psud.fr
Tam LePostdoctoral Researcher at RIKEN AIPVerified email at iip.ist.i.kyoto-u.ac.jp
Andy NguyenStanford UniversityVerified email at stanford.edu
Jean-Luc StarckCEA, Département d'AstrophysiqueVerified email at cea.fr

Marco Cuturi

Google Brain / CREST-ENSAE.

Verified email at google.com - Homepage

machine learning optimal transport kernel methods


Title	Cited by	Year
Sinkhorn Distances: Lightspeed Computation of Optimal Transport M Cuturi Advances in Neural Information Processing Systems, 2292-2300, 2013	742	2013
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	327	2015
Fast computation of wasserstein barycenters M Cuturi, A Doucet Proceedings of the International Conference on Machine Learning 2014, JMLR …, 2014	284	2014
Computational Optimal Transport G Peyré, M Cuturi Foundations and Trends in Machine Learning 11 (5-6), pp. 355-607, 2019	278	2019
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	257	2015
Fast global alignment kernels M Cuturi International Conference in Machine Learning 2011, 2011	221	2011
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	202	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	141	2016
Learning Generative Models with Sinkhorn Divergences A Genevay, G Peyré, M Cuturi Proceedings of the Twenty-First International Conference on Artifical …, 2017	109	2017
Semigroup kernels on measures M Cuturi, K Fukumizu, JP Vert Journal of Machine Learning Research 6 (Jul), 1169-1198, 2005	102	2005
A smoothed dual approach for variational wasserstein problems M Cuturi, G Peyré SIAM J. Imaging Sciences 9 (1), 320–343, 2016	87	2016
Fast dictionary learning with a smoothed Wasserstein loss A Rolet, M Cuturi, G Peyré Artificial Intelligence and Statistics, 630-638, 2016	73	2016
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	64	2017
Ground Metric Learning M Cuturi, D Avis Journal of Machine Learning Research 15 (February), 533−564, 2014	63	2014
Sliced wasserstein kernel for persistence diagrams M Carriere, M Cuturi, S Oudot Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017	59	2017
On wasserstein two-sample testing and related families of nonparametric tests A Ramdas, N Trillos, M Cuturi Entropy 19 (2), 47, 2017	56	2017
Principal geodesic analysis for probability measures under the optimal transport metric V Seguy, M Cuturi Advances in Neural Information Processing Systems, 3312-3320, 2015	55	2015
The context-tree kernel for strings M Cuturi, JP Vert Neural Networks 18 (8), 1111-1123, 2005	55	2005
Wasserstein Barycentric Coordinates: Histogram Regression Using Optimal Transport N Bonneel, G Peyré, M Cuturi ACM Transactions on Graphics 35 (4), 2016	50	2016

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