Marco Cuturi

Addressing Misspecification in Simulation-based Inference through Data-driven Calibration ICML 2025 Controlling Language and Diffusion Models by Transporting Activations ICLR 2025 Disentangled Representation Learning with the Gromov-Monge Gap ICLR 2025 Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection ICML 2025 Shielded Diffusion: Generating Novel and Diverse Images using Sparse Repellency ICML 2025 Simple ReFlow: Improved Techniques for Fast Flow Models ICLR 2025 A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport AISTATS 2024 Careful with that Scalpel: Improving Gradient Surgery with an EMA ICML 2024 Contrasting Multiple Representations with the Multi-Marginal Matching Gap ICML 2024 GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics NeurIPS 2024 Learning Elastic Costs to Shape Monge Displacements NeurIPS 2024 On a Neural Implementation of Brenier’s Polar Factorization ICML 2024 Progressive Entropic Optimal Transport Solvers NeurIPS 2024 Structured Transforms Across Spaces with Cost-Regularized Optimal Transport AISTATS 2024 Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps ICML 2023 Rethinking Initialization of the Sinkhorn Algorithm AISTATS 2023 The Monge Gap: A Regularizer to Learn All Transport Maps ICML 2023 The Schrödinger Bridge between Gaussian Measures has a Closed Form AISTATS 2023 Unbalanced Low-rank Optimal Transport Solvers NeurIPS 2023 Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignment JMLR 2022 Debiaser Beware: Pitfalls of Centering Regularized Transport Maps ICML 2022 Efficient and Modular Implicit Differentiation NeurIPS 2022 Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs ICML 2022 Low-rank Optimal Transport: Approximation, Statistics and Debiasing NeurIPS 2022 On the Complexity of Approximating Multimarginal Optimal Transport JMLR 2022 Proximal Optimal Transport Modeling of Population Dynamics AISTATS 2022 Randomized Stochastic Gradient Descent Ascent AISTATS 2022 Supervised Training of Conditional Monge Maps NeurIPS 2022 Equitable and Optimal Transport with Multiple Agents AISTATS 2021 Low-Rank Sinkhorn Factorization ICML 2021 On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification AISTATS 2021 Debiased Sinkhorn barycenters ICML 2020 Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form NeurIPS 2020 Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm NeurIPS 2020 Learning with Differentiable Pertubed Optimizers NeurIPS 2020 Linear Time Sinkhorn Divergences using Positive Features NeurIPS 2020 Missing Data Imputation using Optimal Transport ICML 2020 Precision-Recall Curves Using Information Divergence Frontiers AISTATS 2020 Projection Robust Wasserstein Distance and Riemannian Optimization NeurIPS 2020 Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport AISTATS 2020 Regularized Optimal Transport is Ground Cost Adversarial ICML 2020 Spatio-temporal alignments: Optimal transport through space and time AISTATS 2020 Supervised Quantile Normalization for Low Rank Matrix Factorization ICML 2020 Differentiable Ranking and Sorting using Optimal Transport NeurIPS 2019 Sample Complexity of Sinkhorn Divergences AISTATS 2019 Stochastic Deep Networks ICML 2019 Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections NeurIPS 2019 Subspace Robust Wasserstein Distances ICML 2019 Tree-Sliced Variants of Wasserstein Distances NeurIPS 2019 Unsupervised Hyper-alignment for Multilingual Word Embeddings ICLR 2019 Wasserstein regularization for sparse multi-task regression AISTATS 2019 Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions NeurIPS 2018 Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport NeurIPS 2018 Learning Generative Models with Sinkhorn Divergences AISTATS 2018 Sliced Wasserstein Kernel for Persistence Diagrams ICML 2017 Soft-DTW: a Differentiable Loss Function for Time-Series ICML 2017 Fast Dictionary Learning with a Smoothed Wasserstein Loss AISTATS 2016 Gromov-Wasserstein Averaging of Kernel and Distance Matrices ICML 2016 Stochastic Optimization for Large-scale Optimal Transport NeurIPS 2016 Wasserstein Training of Restricted Boltzmann Machines NeurIPS 2016 Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric NeurIPS 2015 Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations ICML 2015 Fast Computation of Wasserstein Barycenters ICML 2014 Ground Metric Learning JMLR 2014 Generalized Aitchison Embeddings for Histograms ACML 2013 Mean Reversion with a Variance Threshold ICML 2013 Sinkhorn Distances: Lightspeed Computation of Optimal Transport NeurIPS 2013 White Functionals for Anomaly Detection in Dynamical Systems NeurIPS 2009 Kernels on Structured Objects Through Nested Histograms NeurIPS 2006 Semigroup Kernels on Measures JMLR 2005