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Marco Cuturi

According to our database¹, Marco Cuturi authored at least 115 papers between 2004 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of two.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

On csauthors.net:

Bibliography

2024

Controlling Language and Diffusion Models by Transporting Activations.

[BibT_eX]

[DOI]

Pau Rodríguez López

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,

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,

Nicholas Apostoloff

,

,

CoRR, 2024

Simple ReFlow: Improved Techniques for Fast Flow Models.

[BibT_eX]

[DOI]

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,

,

CoRR, 2024

Sparse Repellency for Shielded Generation in Text-to-image Diffusion Models.

[BibT_eX]

[DOI]

Michael Kirchhof

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,

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,

,

CoRR, 2024

Disentangled Representation Learning through Geometry Preservation with the Gromov-Monge Gap.

[BibT_eX]

[DOI]

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Fabian J. Theis

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,

CoRR, 2024

Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions.

[BibT_eX]

[DOI]

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Hadipour Ansari

,

Pavan Kumar Anasosalu Vasu

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CoRR, 2024

Progressive Entropic Optimal Transport Solvers.

[BibT_eX]

[DOI]

Parnian Kassraie

,

Aram-Alexandre Pooladian

,

,

,

Jonathan Niles-Weed

,

CoRR, 2024

Addressing Misspecification in Simulation-based Inference through Data-driven Calibration.

[BibT_eX]

[DOI]

Antoine Wehenkel

,

Juan L. Gamella

,

,

,

Guillermo Sapiro

,

,

Jörn-Henrik Jacobsen

CoRR, 2024

Learning functions on symmetric matrices and point clouds via lightweight invariant features.

[BibT_eX]

[DOI]

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,

,

CoRR, 2024

On a Neural Implementation of Brenier's Polar Factorization.

[BibT_eX]

[DOI]

,

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Contrasting Multiple Representations with the Multi-Marginal Matching Gap.

[BibT_eX]

[DOI]

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,

,

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Careful with that Scalpel: Improving Gradient Surgery with an EMA.

[BibT_eX]

[DOI]

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,

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,

,

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Structured Transforms Across Spaces with Cost-Regularized Optimal Transport.

[BibT_eX]

[DOI]

Othmane Sebbouh

,

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport.

[BibT_eX]

[DOI]

,

,

Michael I. Jordan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Generative Entropic Neural Optimal Transport To Map Within and Across Spaces.

[BibT_eX]

[DOI]

,

,

Fabian J. Theis

,

CoRR, 2023

Simulation-based Inference for Cardiovascular Models.

[BibT_eX]

[DOI]

Antoine Wehenkel

,

,

Andrew C. Miller

,

Guillermo Sapiro

,

,

,

Jörn-Henrik Jacobsen

CoRR, 2023

Learning Costs for Structured Monge Displacements.

[BibT_eX]

[DOI]

,

Aram-Alexandre Pooladian

,

,

,

Jonathan Niles-Weed

,

CoRR, 2023

Unbalanced Low-rank Optimal Transport Solvers.

[BibT_eX]

[DOI]

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,

,

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Monge Gap: A Regularizer to Learn All Transport Maps.

[BibT_eX]

[DOI]

,

Proceedings of the International Conference on Machine Learning, 2023

Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps.

[BibT_eX]

[DOI]

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,

Proceedings of the International Conference on Machine Learning, 2023

Rethinking Initialization of the Sinkhorn Algorithm.

[BibT_eX]

[DOI]

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

The Schrödinger Bridge between Gaussian Measures has a Closed Form.

[BibT_eX]

[DOI]

Charlotte Bunne

,

,

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

On the Complexity of Approximating Multimarginal Optimal Transport.

[BibT_eX]

[DOI]

,

,

,

Michael I. Jordan

J. Mach. Learn. Res., 2022

Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments.

[BibT_eX]

[DOI]

,

,

Alexandre Gramfort

CoRR, 2022

Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges.

[BibT_eX]

[DOI]

Charlotte Bunne

,

,

,

CoRR, 2022

Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein.

[BibT_eX]

[DOI]

,

Laetitia Meng-Papaxanthos

,

,

Charlotte Bunne

,

,

CoRR, 2022

Low-rank Optimal Transport: Approximation, Statistics and Debiasing.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Supervised Training of Conditional Monge Maps.

[BibT_eX]

[DOI]

Charlotte Bunne

,

,

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient and Modular Implicit Differentiation.

[BibT_eX]

[DOI]

Mathieu Blondel

,

Quentin Berthet

,

,

,

,

Felipe Llinares-López

,

Fabian Pedregosa

,

Jean-Philippe Vert

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs.

[BibT_eX]

[DOI]

,

,

Proceedings of the International Conference on Machine Learning, 2022

Debiaser Beware: Pitfalls of Centering Regularized Transport Maps.

[BibT_eX]

[DOI]

Aram-Alexandre Pooladian

,

,

Jonathan Niles-Weed

Proceedings of the International Conference on Machine Learning, 2022

Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport.

[BibT_eX]

[DOI]

,

,

Proceedings of the 13th International Conference on Computational Creativity, Bozen-Bolzano, Italy, June 27, 2022

Randomized Stochastic Gradient Descent Ascent.

[BibT_eX]

[DOI]

Othmane Sebbouh

,

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Proximal Optimal Transport Modeling of Population Dynamics.

[BibT_eX]

[DOI]

Charlotte Bunne

,

Laetitia Papaxanthos

,

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Ground Metric Learning on Graphs.

[BibT_eX]

[DOI]

,

Nicolas Bonneel

,

David Coeurjolly

,

,

J. Math. Imaging Vis., 2021

JKOnet: Proximal Optimal Transport Modeling of Population Dynamics.

[BibT_eX]

[DOI]

Charlotte Bunne

,

Laetitia Meng-Papaxanthos

,

,

CoRR, 2021

Low-Rank Sinkhorn Factorization.

[BibT_eX]

[DOI]

,

,

Proceedings of the 38th International Conference on Machine Learning, 2021

Equitable and Optimal Transport with Multiple Agents.

[BibT_eX]

[DOI]

,

Laurent Meunier

,

,

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification.

[BibT_eX]

[DOI]

,

,

,

,

Michael I. Jordan

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Multi-subject MEG/EEG source imaging with sparse multi-task regression.

[BibT_eX]

[DOI]

,

Thomas Bazeille

,

Bertrand Thirion

,

,

Alexandre Gramfort

NeuroImage, 2020

Handling Multiple Costs in Optimal Transport: Strong Duality and Efficient Computation.

[BibT_eX]

[DOI]

,

Laurent Meunier

,

,

CoRR, 2020

Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design.

[BibT_eX]

[DOI]

,

,

Jean-Philippe Vert

CoRR, 2020

Learning with Differentiable Perturbed Optimizers.

[BibT_eX]

[DOI]

Quentin Berthet

,

Mathieu Blondel

,

,

,

Jean-Philippe Vert

,

Francis R. Bach

CoRR, 2020

Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms.

[BibT_eX]

[DOI]

,

,

,

,

Michael I. Jordan

CoRR, 2020

Supervised Quantile Normalization for Low-rank Matrix Approximation.

[BibT_eX]

[DOI]

,

,

Jonathan Niles-Weed

,

Jean-Philippe Vert

CoRR, 2020

Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces.

[BibT_eX]

[DOI]

,

,

,

Hisashi Kashima

CoRR, 2020

Linear Time Sinkhorn Divergences using Positive Features.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm.

[BibT_eX]

[DOI]

,

,

,

,

Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Projection Robust Wasserstein Distance and Riemannian Optimization.

[BibT_eX]

[DOI]

,

,

,

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Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form.

[BibT_eX]

[DOI]

,

,

,

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning with Differentiable Pertubed Optimizers.

[BibT_eX]

[DOI]

Quentin Berthet

,

Mathieu Blondel

,

,

,

Jean-Philippe Vert

,

Francis R. Bach

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Regularized Optimal Transport is Ground Cost Adversarial.

[BibT_eX]

[DOI]

François-Pierre Paty

,

Proceedings of the 37th International Conference on Machine Learning, 2020

Missing Data Imputation using Optimal Transport.

[BibT_eX]

[DOI]

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,

,

Proceedings of the 37th International Conference on Machine Learning, 2020

Debiased Sinkhorn barycenters.

[BibT_eX]

[DOI]

,

,

Alexandre Gramfort

Proceedings of the 37th International Conference on Machine Learning, 2020

Supervised Quantile Normalization for Low Rank Matrix Factorization.

[BibT_eX]

[DOI]

,

,

Jonathan Niles-Weed

,

Jean-Philippe Vert

Proceedings of the 37th International Conference on Machine Learning, 2020

Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport.

[BibT_eX]

[DOI]

François-Pierre Paty

,

Alexandre d'Aspremont

,

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Spatio-temporal alignments: Optimal transport through space and time.

[BibT_eX]

[DOI]

,

,

Alexandre Gramfort

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Precision-Recall Curves Using Information Divergence Frontiers.

[BibT_eX]

[DOI]

,

,

,

,

Olivier Bousquet

,

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Information Geometry for Regularized Optimal Transport and Barycenters of Patterns.

[BibT_eX]

[DOI]

Shun-ichi Amari

,

,

Masafumi Oizumi

,

Neural Comput., 2019

Computational Optimal Transport.

[BibT_eX]

[DOI]

,

Found. Trends Mach. Learn., 2019

Deep multi-class learning from label proportions.

[BibT_eX]

[DOI]

Gabriel Dulac-Arnold

,

,

,

,

Jean-Philippe Vert

CoRR, 2019

Differentiable Sorting using Optimal Transport: The Sinkhorn CDF and Quantile Operator.

[BibT_eX]

[DOI]

,

,

Jean-Philippe Vert

CoRR, 2019

Evaluating Generative Models Using Divergence Frontiers.

[BibT_eX]

[DOI]

,

,

,

,

Olivier Bousquet

,

CoRR, 2019

Tree-Sliced Approximation of Wasserstein Distances.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2019

Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Tree-Sliced Variants of Wasserstein Distances.

[BibT_eX]

[DOI]

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,

,

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Differentiable Ranking and Sorting using Optimal Transport.

[BibT_eX]

[DOI]

,

,

Jean-Philippe Vert

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates.

[BibT_eX]

[DOI]

,

Thomas Bazeille

,

Bertrand Thirion

,

,

Alexandre Gramfort

Proceedings of the Information Processing in Medical Imaging, 2019

Subspace Robust Wasserstein Distances.

[BibT_eX]

[DOI]

François-Pierre Paty

,

Proceedings of the 36th International Conference on Machine Learning, 2019

Stochastic Deep Networks.

[BibT_eX]

[DOI]

Gwendoline de Bie

,

,

Proceedings of the 36th International Conference on Machine Learning, 2019

Unsupervised Hyper-alignment for Multilingual Word Embeddings.

[BibT_eX]

[DOI]

,

,

,

Proceedings of the 7th International Conference on Learning Representations, 2019

Wasserstein regularization for sparse multi-task regression.

[BibT_eX]

[DOI]

,

,

Alexandre Gramfort

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Sample Complexity of Sinkhorn Divergences.

[BibT_eX]

[DOI]

,

Lénaïc Chizat

,

Francis R. Bach

,

,

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Geodesic PCA versus Log-PCA of Histograms in the Wasserstein Space.

[BibT_eX]

[DOI]

,

,

Jérémie Bigot

,

,

Nicolas Papadakis

SIAM J. Sci. Comput., 2018

Semidual Regularized Optimal Transport.

[BibT_eX]

[DOI]

,

SIAM Rev., 2018

Wasserstein Dictionary Learning: Optimal Transport-Based Unsupervised Nonlinear Dictionary Learning.

[BibT_eX]

[DOI]

Morgan A. Schmitz

,

,

Nicolas Bonneel

,

Fred Maurice Ngolè Mboula

,

David Coeurjolly

,

,

,

Jean-Luc Starck

SIAM J. Imaging Sci., 2018

Wasserstein discriminant analysis.

[BibT_eX]

[DOI]

,

,

,

Alain Rakotomamonjy

Mach. Learn., 2018

Semi-dual Regularized Optimal Transport.

[BibT_eX]

[DOI]

,

CoRR, 2018

Unsupervised Hyperalignment for Multilingual Word Embeddings.

[BibT_eX]

[DOI]

,

,

,

CoRR, 2018

Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport.

[BibT_eX]

[DOI]

,

,

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Generative Models with Sinkhorn Divergences.

[BibT_eX]

[DOI]

,

,

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests.

[BibT_eX]

[DOI]

,

Nicolás García Trillos

,

Entropy, 2017

Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning.

[BibT_eX]

[DOI]

Morgan A. Schmitz

,

,

Nicolas Bonneel

,

Fred Maurice Ngolè Mboula

,

David Coeurjolly

,

,

,

Jean-Luc Starck

CoRR, 2017

Soft-DTW: a Differentiable Loss Function for Time-Series.

[BibT_eX]

[DOI]

,

Mathieu Blondel

Proceedings of the 34th International Conference on Machine Learning, 2017

Sliced Wasserstein Kernel for Persistence Diagrams.

[BibT_eX]

[DOI]

Mathieu Carrière

,

,

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Wasserstein barycentric coordinates: histogram regression using optimal transport.

[BibT_eX]

[DOI]

Nicolas Bonneel

,

,

ACM Trans. Graph., 2016

A Smoothed Dual Approach for Variational Wasserstein Problems.

[BibT_eX]

[DOI]

,

SIAM J. Imaging Sci., 2016

Wasserstein Training of Restricted Boltzmann Machines.

[BibT_eX]

[DOI]

Grégoire Montavon

,

Klaus-Robert Müller

,

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Stochastic Optimization for Large-scale Optimal Transport.

[BibT_eX]

[DOI]

,

,

,

Francis R. Bach

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Gromov-Wasserstein Averaging of Kernel and Distance Matrices.

[BibT_eX]

[DOI]

,

,

Proceedings of the 33nd International Conference on Machine Learning, 2016

Fast Dictionary Learning with a Smoothed Wasserstein Loss.

[BibT_eX]

[DOI]

,

,

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Convolutional wasserstein distances: efficient optimal transportation on geometric domains.

[BibT_eX]

[DOI]

,

Fernando de Goes

,

,

,

Adrian Butscher

,

,

,

Leonidas J. Guibas

ACM Trans. Graph., 2015

Iterative Bregman Projections for Regularized Transportation Problems.

[BibT_eX]

[DOI]

Jean-David Benamou

,

Guillaume Carlier

,

,

,

SIAM J. Sci. Comput., 2015

Adaptive Euclidean maps for histograms: generalized Aitchison embeddings.

[BibT_eX]

[DOI]

,

Mach. Learn., 2015

Wasserstein Training of Boltzmann Machines.

[BibT_eX]

[DOI]

Grégoire Montavon

,

Klaus-Robert Müller

,

CoRR, 2015

Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Fast Optimal Transport Averaging of Neuroimaging Data.

[BibT_eX]

[DOI]

Alexandre Gramfort

,

,

Proceedings of the Information Processing in Medical Imaging, 2015

Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations.

[BibT_eX]

[DOI]

,

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Ground metric learning.

[BibT_eX]

[DOI]

,

J. Mach. Learn. Res., 2014

Fast Computation of Wasserstein Barycenters.

[BibT_eX]

[DOI]

,

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Sinkhorn Distances: Lightspeed Computation of Optimal Transport.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Mean Reversion with a Variance Threshold.

[BibT_eX]

[DOI]

,

Alexandre d'Aspremont

Proceedings of the 30th International Conference on Machine Learning, 2013

Generalized Aitchison Embeddings for Histograms.

[BibT_eX]

[DOI]

,

Proceedings of the Asian Conference on Machine Learning, 2013

2011

PEMS-SF.

[BibT_eX]

[DOI]

Dataset, May, 2011

Mapping kernels for trees.

[BibT_eX]

[DOI]

,

,

Tetsuji Kuboyama

Proceedings of the 28th International Conference on Machine Learning, 2011

Fast Global Alignment Kernels.

[BibT_eX]

[DOI]

Proceedings of the 28th International Conference on Machine Learning, 2011

2009

White Functionals for Anomaly Detection in Dynamical Systems.

[BibT_eX]

[DOI]

,

Jean-Philippe Vert

,

Alexandre d'Aspremont

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007

Permanents, Transport Polytopes and Positive Definite Kernels on Histograms.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2007, 2007

A Kernel for Time Series Based on Global Alignments.

[BibT_eX]

[DOI]

,

Jean-Philippe Vert

,

Øystein Birkenes

,

Proceedings of the IEEE International Conference on Acoustics, 2007

2006

Shot Boundary Detection and High-Level Feature Extraction Experiments for TRECVID 2006.

[BibT_eX]

[DOI]

,

Kazunori Matsumoto

,

Masami Shishibori

,

,

,

,

Shin'ichi Satoh

,

Keiichiro Hoashi

,

,

Yasuyuki Nakajima

Proceedings of the 2006 TREC Video Retrieval Evaluation, 2006

Kernels on Structured Objects Through Nested Histograms.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

The context-tree kernel for strings.

[BibT_eX]

[DOI]

,

Jean-Philippe Vert

Neural Networks, 2005

Semigroup Kernels on Measures.

[BibT_eX]

[DOI]

,

,

Jean-Philippe Vert

J. Mach. Learn. Res., 2005

Multiresolution Kernels

[BibT_eX]

[DOI]

,

CoRR, 2005

2004

Semigroup Kernels on Finite Sets.

[BibT_eX]

[DOI]

,

Jean-Philippe Vert

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

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