Marco Cuturi

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Gabriel PeyréCNRS, DMA, Ecole Normale SupérieureVerified email at ens.fr
Jean-Philippe VertOwkin / PSL UniversityVerified email at mines-paristech.fr
Aude GenevayMITVerified email at mit.edu
Justin SolomonMITVerified email at mit.edu
Alexandre GramfortMetaVerified email at meta.com
Olivier TeboulTherapanaceaVerified email at therapanacea.eu
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Arnaud DoucetProfessor of Statistics, University of Oxford & Senior Research Scientist, Google DeepMindVerified email at stats.ox.ac.uk
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Tianyi LinUniversity of California, BerkeleyVerified email at berkeley.edu
Nicolas BonneelCNRS / LIRIS / Univ. LyonVerified email at liris.cnrs.fr
Mathieu BlondelGoogleVerified email at google.com
Hicham JanatiAssociate professor, Télécom ParisVerified email at telecom-paris.fr
Nhat HoProfessor at University of Texas, AustinVerified email at utexas.edu
Fernando de GoesPixar Animation StudiosVerified email at pixar.com
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Adrian ButscherAutodeskVerified email at autodesk.com
Tao DuInstitute for Interdisciplinary Information Sciences (IIIS), Tsinghua UniversityVerified email at tsinghua.edu.cn
Boris MuzellecOwkinVerified email at owkin.com
Matthieu HeitzCNRS, Université Lyon 1Verified email at univ-lyon1.fr

Marco Cuturi

Apple / CREST-ENSAE.

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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	2810	2013
Computational Optimal Transport G Peyré, M Cuturi Foundations and Trends in Machine Learning 11 (5-6), pp. 355-607, 2019	1985	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	702	2015
Fast computation of Wasserstein barycenters M Cuturi, A Doucet Proceedings of the International Conference on Machine Learning 2014, JMLR …, 2014	655	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	594	2015
Learning Generative Models with Sinkhorn Divergences A Genevay, G Peyré, M Cuturi Proceedings of the Twenty-First International Conference on Artifical …, 2017	563*	2017
Soft-DTW: a differentiable loss function for time-series M Cuturi, M Blondel Proceedings of the 34th International Conference on Machine Learning, PMLR …, 2017	464	2017
Stochastic optimization for large-scale optimal transport A Genevay, M Cuturi, G Peyré, F Bach arXiv preprint arXiv:1605.08527, 2016	405	2016
Fast global alignment kernels M Cuturi International Conference in Machine Learning 2011, 2011	396	2011
On wasserstein two-sample testing and related families of nonparametric tests A Ramdas, N García Trillos, M Cuturi Entropy 19 (2), 47, 2017	329	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	287	2007
Gromov-wasserstein averaging of kernel and distance matrices G Peyré, M Cuturi, J Solomon International conference on machine learning, 2664-2672, 2016	242	2016
Sliced Wasserstein kernel for persistence diagrams M Carriere, M Cuturi, S Oudot International conference on machine learning, 664-673, 2017	225	2017
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	206	2019
A smoothed dual approach for variational wasserstein problems M Cuturi, G Peyré SIAM J. Imaging Sciences 9 (1), 320–343, 2016	185	2016
Wasserstein Barycentric Coordinates: Histogram Regression Using Optimal Transport N Bonneel, G Peyré, M Cuturi ACM Transactions on Graphics 35 (4), 2016	151	2016
Fast dictionary learning with a smoothed Wasserstein loss A Rolet, M Cuturi, G Peyré Artificial Intelligence and Statistics, 630-638, 2016	143	2016
Wasserstein dictionary learning: Optimal transport-based unsupervised nonlinear dictionary learning MA Schmitz, M Heitz, N Bonneel, F Ngole, D Coeurjolly, M Cuturi, G Peyré, ... SIAM Journal on Imaging Sciences 11 (1), 643-678, 2018	130	2018
Wasserstein training of restricted Boltzmann machines G Montavon, KR Müller, M Cuturi Advances in Neural Information Processing Systems 29, 2016	123*	2016
Learning with differentiable perturbed optimizers Q Berthet, M Blondel, O Teboul, M Cuturi, JP Vert, F Bach NeurIPS 2020, 2020	114	2020

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