Cuturi, Marco

80 publications

ICML 2025 Addressing Misspecification in Simulation-Based Inference Through Data-Driven Calibration Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Joern-Henrik Jacobsen, Marco Cuturi

ICLR 2025 Controlling Language and Diffusion Models by Transporting Activations Pau Rodriguez, Arno Blaas, Michal Klein, Luca Zappella, Nicholas Apostoloff, Marco Cuturi, Xavier Suau

ICLR 2025 Disentangled Representation Learning with the Gromov-Monge Gap Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J Theis, Zeynep Akata, Marco Cuturi

NeurIPS 2025 LinEAS: End-to-End Learning of Activation Steering with a Distributional Loss Pau Rodriguez, Michal Klein, Eleonora Gualdoni, Valentino Maiorca, Arno Blaas, Luca Zappella, Marco Cuturi, Xavier Suau

NeurIPS 2025 Sample and mAP from a Single Convex Potential: Generation Using Conjugate Moment Measures Nina Vesseron, Louis Béthune, Marco Cuturi

ICML 2025 Scaling Laws for Forgetting During Finetuning with Pretraining Data Injection Louis Béthune, David Grangier, Dan Busbridge, Eleonora Gualdoni, Marco Cuturi, Pierre Ablin

ICML 2025 Shielded Diffusion: Generating Novel and Diverse Images Using Sparse Repellency Michael Kirchhof, James Thornton, Louis Béthune, Pierre Ablin, Eugene Ndiaye, Marco Cuturi

ICLR 2025 Simple ReFlow: Improved Techniques for Fast Flow Models Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye, Bahjat Kawar, James Thornton

AISTATS 2024 A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport Tianyi Lin, Marco Cuturi, Michael Jordan

ICML 2024 Careful with That Scalpel: Improving Gradient Surgery with an EMA Yu-Guan Hsieh, James Thornton, Eugene Ndiaye, Michal Klein, Marco Cuturi, Pierre Ablin

ICML 2024 Contrasting Multiple Representations with the Multi-Marginal Matching Gap Zoe Piran, Michal Klein, James Thornton, Marco Cuturi

ICMLW 2024 Disentangled Representation Learning Through Geometry Preservation with the Gromov-Monge Gap Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J Theis, Zeynep Akata, Marco Cuturi

NeurIPS 2024 GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics Dominik Klein, Théo Uscidda, Fabian Theis, Marco Cuturi

NeurIPSW 2024 Galois Features: Nearly-Complete Invariants on Symmetric Matrices Ben Blum-Smith, Ningyuan Teresa Huang, Marco Cuturi, Soledad Villar

NeurIPS 2024 Learning Elastic Costs to Shape Monge Displacements Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi

ICML 2024 On a Neural Implementation of Brenier’s Polar Factorization Nina Vesseron, Marco Cuturi

NeurIPS 2024 Progressive Entropic Optimal Transport Solvers Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi

AISTATS 2024 Structured Transforms Across Spaces with Cost-Regularized Optimal Transport Othmane Sebbouh, Marco Cuturi, Gabriel Peyré

ICML 2023 Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps Marco Cuturi, Michal Klein, Pierre Ablin

AISTATS 2023 Rethinking Initialization of the Sinkhorn Algorithm James Thornton, Marco Cuturi

ICML 2023 The Monge Gap: A Regularizer to Learn All Transport Maps Théo Uscidda, Marco Cuturi

AISTATS 2023 The Schrödinger Bridge Between Gaussian Measures Has a Closed Form Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause

NeurIPS 2023 Unbalanced Low-Rank Optimal Transport Solvers Meyer Scetbon, Michal Klein, Giovanni Palla, Marco Cuturi

AISTATS 2022 Proximal Optimal Transport Modeling of Population Dynamics Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause, Marco Cuturi

AISTATS 2022 Randomized Stochastic Gradient Descent Ascent Othmane Sebbouh, Marco Cuturi, Gabriel Peyré

ICML 2022 Debiaser Beware: Pitfalls of Centering Regularized Transport Maps Aram-Alexandre Pooladian, Marco Cuturi, Jonathan Niles-Weed

NeurIPS 2022 Efficient and Modular Implicit Differentiation Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-Lopez, Fabian Pedregosa, Jean-Philippe Vert

ICML 2022 Linear-Time Gromov Wasserstein Distances Using Low Rank Couplings and Costs Meyer Scetbon, Gabriel Peyré, Marco Cuturi

NeurIPS 2022 Low-Rank Optimal Transport: Approximation, Statistics and Debiasing Meyer Scetbon, Marco Cuturi

JMLR 2022 On the Complexity of Approximating Multimarginal Optimal Transport Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan

NeurIPS 2022 Supervised Training of Conditional Monge Maps Charlotte Bunne, Andreas Krause, Marco Cuturi

AISTATS 2021 Equitable and Optimal Transport with Multiple Agents Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi

AISTATS 2021 On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification Tianyi Lin, Zeyu Zheng, Elynn Chen, Marco Cuturi, Michael I. Jordan

ICML 2021 Low-Rank Sinkhorn Factorization Meyer Scetbon, Marco Cuturi, Gabriel Peyré

ICML 2020 Debiased Sinkhorn Barycenters Hicham Janati, Marco Cuturi, Alexandre Gramfort

NeurIPS 2020 Entropic Optimal Transport Between Unbalanced Gaussian Measures Has a Closed Form Hicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi

NeurIPS 2020 Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan

NeurIPS 2020 Learning with Differentiable Pertubed Optimizers Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach

NeurIPS 2020 Linear Time Sinkhorn Divergences Using Positive Features Meyer Scetbon, Marco Cuturi

ICML 2020 Missing Data Imputation Using Optimal Transport Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi

AISTATS 2020 Precision-Recall Curves Using Information Divergence Frontiers Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly

NeurIPS 2020 Projection Robust Wasserstein Distance and Riemannian Optimization Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan

AISTATS 2020 Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport François-Pierre Paty, Alexandre d’Aspremont, Marco Cuturi

ICML 2020 Regularized Optimal Transport Is Ground Cost Adversarial François-Pierre Paty, Marco Cuturi

AISTATS 2020 Spatio-Temporal Alignments: Optimal Transport Through Space and Time Hicham Janati, Marco Cuturi, Alexandre Gramfort

ICML 2020 Supervised Quantile Normalization for Low Rank Matrix Factorization Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert

FnTML 2019 Computational Optimal Transport Gabriel Peyré, Marco Cuturi

NeurIPS 2019 Differentiable Ranking and Sorting Using Optimal Transport Marco Cuturi, Olivier Teboul, Jean-Philippe Vert

AISTATS 2019 Sample Complexity of Sinkhorn Divergences Aude Genevay, Lénaïc Chizat, Francis Bach, Marco Cuturi, Gabriel Peyré

ICML 2019 Stochastic Deep Networks Gwendoline De Bie, Gabriel Peyré, Marco Cuturi

NeurIPS 2019 Subspace Detours: Building Transport Plans That Are Optimal on Subspace Projections Boris Muzellec, Marco Cuturi

ICML 2019 Subspace Robust Wasserstein Distances François-Pierre Paty, Marco Cuturi

NeurIPS 2019 Tree-Sliced Variants of Wasserstein Distances Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi

ICLR 2019 Unsupervised Hyper-Alignment for Multilingual Word Embeddings Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin

AISTATS 2019 Wasserstein Regularization for Sparse Multi-Task Regression Hicham Janati, Marco Cuturi, Alexandre Gramfort

NeurIPS 2018 Generalizing Point Embeddings Using the Wasserstein Space of Elliptical Distributions Boris Muzellec, Marco Cuturi

NeurIPS 2018 Large Scale Computation of Means and Clusters for Persistence Diagrams Using Optimal Transport Theo Lacombe, Marco Cuturi, Steve Oudot

AISTATS 2018 Learning Generative Models with Sinkhorn Divergences Aude Genevay, Gabriel Peyré, Marco Cuturi

MLJ 2018 Wasserstein Discriminant Analysis Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy

ICML 2017 Sliced Wasserstein Kernel for Persistence Diagrams Mathieu Carrière, Marco Cuturi, Steve Oudot

ICML 2017 Soft-DTW: A Differentiable Loss Function for Time-Series Marco Cuturi, Mathieu Blondel

AISTATS 2016 Fast Dictionary Learning with a Smoothed Wasserstein Loss Antoine Rolet, Marco Cuturi, Gabriel Peyré

ICML 2016 Gromov-Wasserstein Averaging of Kernel and Distance Matrices Gabriel Peyré, Marco Cuturi, Justin Solomon

NeurIPS 2016 Stochastic Optimization for Large-Scale Optimal Transport Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis Bach

NeurIPS 2016 Wasserstein Training of Restricted Boltzmann Machines Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi

MLJ 2015 Adaptive Euclidean Maps for Histograms: Generalized Aitchison Embeddings Tam Le, Marco Cuturi

NeurIPS 2015 Principal Geodesic Analysis for Probability Measures Under the Optimal Transport Metric Vivien Seguy, Marco Cuturi

ICML 2015 Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations Tam Le, Marco Cuturi

ICML 2014 Fast Computation of Wasserstein Barycenters Marco Cuturi, Arnaud Doucet

JMLR 2014 Ground Metric Learning Marco Cuturi, David Avis

ACML 2013 Generalized Aitchison Embeddings for Histograms Tam Le, Marco Cuturi

ICML 2013 Mean Reversion with a Variance Threshold Marco Cuturi, Alexandre D’Aspremont

NeurIPS 2013 Sinkhorn Distances: Lightspeed Computation of Optimal Transport Marco Cuturi

ICML 2011 Fast Global Alignment Kernels Marco Cuturi

ICML 2011 Mapping Kernels for Trees Kilho Shin, Marco Cuturi, Tetsuji Kuboyama

NeurIPS 2009 White Functionals for Anomaly Detection in Dynamical Systems Marco Cuturi, Jean-philippe Vert, Alexandre D'aspremont

IJCAI 2007 Permanents, Transport Polytopes and Positive Definite Kernels on Histograms Marco Cuturi

NeurIPS 2006 Kernels on Structured Objects Through Nested Histograms Marco Cuturi, Kenji Fukumizu

JMLR 2005 Semigroup Kernels on Measures Marco Cuturi, Kenji Fukumizu, Jean-Philippe Vert

NeurIPS 2004 Semigroup Kernels on Finite Sets Marco Cuturi, Jean-philippe Vert