Cuturi, Marco
- Learning with Differentiable Perturbed Optimizers
2020/02/20 by Quentin Berthet, Mathieu Blondel, Berthet, Quentin +9 · 4 voices · 6 citations
#cs.LG #math.OC #stat.ML
- Soft-DTW: a Differentiable Loss Function for Time-Series
2017/03/05 by Marco Cuturi, Mathieu Blondel, Cuturi, Marco +1 · 39 citations
Computer Science · #Time Series Analysis and Forecasting #Music and Audio Processing #Advanced Text Analysis Techniques
- Iterative Bregman Projections for Regularized Transportation Problems
2014/12/16 by Benamou, Jean-David, Carlier, Guillaume, Cuturi, Marco +2 · 33 citations
#Analysis of PDEs (math.AP) #FOS: Mathematics #Numerical Analysis (math.NA)
- Learning Generative Models with Sinkhorn Divergences
2017/06/01 by Aude Genevay, Genevay, Aude, Gabriel Peyré +3 · 32 citations
Computer Science · #Generative Adversarial Networks and Image Synthesis #Multimodal Machine Learning Applications #Face recognition and analysis
- Stochastic Optimization for Large-scale Optimal Transport
2016/05/27 by Aude Genevay, Marco Cuturi, Aude, Genevay +5 · 29 citations
Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques #Gaussian Processes and Bayesian Inference
- Efficient and Modular Implicit Differentiation
2021/05/31 by Blondel, Mathieu, Berthet, Quentin, Cuturi, Marco +5 · 29 citations
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
- On Wasserstein Two Sample Testing and Related Families of Nonparametric\n Tests
2015/09/07 by Aaditya Ramdas, Ramdas, Aaditya, N. Garcı́a +3 · 20 citations
Computer Science · Mathematics · #Advanced Statistical Methods and Models #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistical Methods and Inference #Statistics Theory (math.ST)
- Sample Complexity of Sinkhorn divergences
2018/10/05 by Aude Genevay, Genevay, Aude, Lénaïc Chizat +7 · 29 citations
Computer Science · Decision Sciences · #Adversarial Robustness in Machine Learning #FOS: Mathematics #Machine Learning and Algorithms #Probabilistic and Robust Engineering Design #Statistics Theory (math.ST)
- Sliced Wasserstein Kernel for Persistence Diagrams
2017/06/11 by Mathieu Carrière, Carrière, Mathieu, Marco Cuturi +3 · 10 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Algebraic Topology (math.AT) #Cell Image Analysis Techniques #Computational Geometry (cs.CG) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Morphological variations and asymmetry #Topological and Geometric Data Analysis
- The Schrödinger Bridge between Gaussian Measures has a Closed Form
2022/02/11 by Charlotte Bunne, Ya‐Ping Hsieh, Bunne, Charlotte +5 · 13 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Cancer Genomics and Diagnostics #FOS: Biological sciences #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Quantitative Methods (q-bio.QM) #Single-cell and spatial transcriptomics
- Missing Data Imputation using Optimal Transport
2020/02/10 by Muzellec, Boris, Josse, Julie, Boyer, Claire +1 · 10 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Differentiable Ranks and Sorting using Optimal Transport
2019/05/28 by Marco Cuturi, Olivier Teboul, Cuturi, Marco +3 · 8 citations
Computer Science · #Machine Learning and Algorithms #Machine Learning and Data Classification #Bayesian Methods and Mixture Models
- Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein
2022/01/28 by Marco Cuturi, Cuturi, Marco, Laetitia Meng-Papaxanthos +9 · 9 citations
Engineering · Materials Science · #Asphalt Pavement Performance Evaluation #Electron and X-Ray Spectroscopy Techniques
- Low-Rank Sinkhorn Factorization
2021/03/08 by Scetbon, Meyer, Cuturi, Marco, Peyré, Gabriel · 7 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Controlling Language and Diffusion Models by Transporting Activations
2024/10/30 by Pau Rodriguez, Pau Rodríguez, Arno Blaas +12 · 2 voices · 8 citations
Computer Science · #Natural Language Processing Techniques #cs.AI #cs.CL #cs.CV #cs.LG
- Principal Geodesic Analysis for Probability Measures under the Optimal\n Transport Metric
2015/06/25 by Vivien Seguy, Seguy, Vivien, Marco Cuturi +1 · 5 citations
Computer Science · Engineering · Mathematics · #Topological and Geometric Data Analysis #3D Shape Modeling and Analysis #Point processes and geometric inequalities
- Simple ReFlow: Improved Techniques for Fast Flow Models
2024/10/10 by Beomsu Kim, Kim, Beomsu, Yu-Guan Hsieh +11 · 1 voice · 12 citations
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.CV #cs.LG
- Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
2024/05/14 by Antoine Wehenkel, Wehenkel, Antoine, Juan L. Gamella +12 · 1 voice · 8 citations
Decision Sciences · #Simulation Techniques and Applications #cs.LG #stat.ME #stat.ML
- Projection Robust Wasserstein Distance and Riemannian Optimization
2020/06/12 by Tianyi Lin, Lin, Tianyi, Chenyou Fan +7 · 5 citations
Computer Science · Engineering · Mathematics · #Advanced Image Processing Techniques #FOS: Computer and information sciences #FOS: Mathematics #Geometric Analysis and Curvature Flows #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
- GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics
2023/10/13 by Dominik Klein, Théo Uscidda, Klein, Dominik +5 · 1 voice · 6 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
- Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport
2018/05/22 by Théo Lacombe, Marco Cuturi, Lacombe, Théo +3 · 4 citations
Computer Science · Mathematics · #Advanced Graph Neural Networks #Computational Geometry (cs.CG) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Topological and Geometric Data Analysis
- A Smoothed Dual Approach for Variational Wasserstein Problems
2015/03/09 by Marco Cuturi, Cuturi, Marco, Gabriel Peyré +1 · 3 citations
Computer Science · Mathematics · #Advanced Image Processing Techniques #FOS: Computer and information sciences #FOS: Mathematics #Geometric Analysis and Curvature Flows #Machine Learning (stat.ML) #Optimization and Control (math.OC)
- Fast Optimal Transport Averaging of Neuroimaging Data
2015/03/30 by Gramfort, Alexandre, Peyré, Gabriel, Cuturi, Marco · 3 citations
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
- Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
2021/06/02 by Scetbon, Meyer, Peyré, Gabriel, Cuturi, Marco · 4 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Supervised Training of Conditional Monge Maps
2022/06/28 by Charlotte Bunne, Bunne, Charlotte, Andreas Krause +3 · 4 citations
Computer Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Healthcare
- Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces
2020/02/05 by Ryoma Sato, Sato, Ryoma, Marco Cuturi +5 · 3 citations
Computer Science · #Advanced Clustering Algorithms Research #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Stochastic Deep Networks
2018/11/19 by de Bie, Gwendoline, Peyré, Gabriel, Cuturi, Marco · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Wasserstein Training of Boltzmann Machines
2015/07/07 by Grégoire Montavon, Klaus‐Robert Müller, Montavon, Grégoire +3 · 3 citations
Computer Science · Engineering · Physics and Astronomy · #Generative Adversarial Networks and Image Synthesis #Lattice Boltzmann Simulation Studies #Model Reduction and Neural Networks
- Multivariate Conformal Prediction using Optimal Transport
2025/02/05 by Michal Klein, Louis Béthune, Klein, Michal +5 · 10 citations
Computer Science · #Neural Networks and Applications
- Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
2025/02/09 by Louis Béthune, Bethune, Louis, David Grangier +9 · 9 citations
Computer Science · #Computation and Language (cs.CL) #Computer Graphics and Visualization Techniques #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Neural Networks and Applications
- Low-rank Optimal Transport: Approximation, Statistics and Debiasing
2022/05/24 by Meyer Scetbon, Scetbon, Meyer, Marco Cuturi +1 · 3 citations
Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Gaussian Processes and Bayesian Inference #Distributed Sensor Networks and Detection Algorithms
- Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections
2019/05/24 by Muzellec, Boris, Cuturi, Marco · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- On the Complexity of Approximating Multimarginal Optimal Transport
2019/09/30 by Lin, Tianyi, Ho, Nhat, Cuturi, Marco +1 · 2 citations
#Computation (stat.CO) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
- Structured Transforms Across Spaces with Cost-Regularized Optimal Transport
2023/11/09 by Othmane Sebbouh, Marco Cuturi, Sebbouh, Othmane +3 · 3 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Probabilistic and Robust Engineering Design #Single-cell and spatial transcriptomics
- The Monge Gap: A Regularizer to Learn All Transport Maps
2023/02/09 by Uscidda, Théo, Cuturi, Marco · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
2020/06/22 by Tianyi Lin, Zeyu Zheng, Lin, Tianyi +7 · 2 citations
Computer Science · Decision Sciences · Environmental Science · Mathematics · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #FOS: Mathematics #Groundwater flow and contamination studies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Probabilistic and Robust Engineering Design #Statistics Theory (math.ST)
- Learning Elastic Costs to Shape Monge Displacements
2023/06/20 by Michal Klein, Klein, Michal, Aram-Alexandre Pooladian +9 · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Wasserstein regularization for sparse multi-task regression
2018/05/20 by Janati, Hicham, Cuturi, Marco, Gramfort, Alexandre · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Shielded Diffusion: Generating Novel and Diverse Images using Sparse Repellency
2024/10/08 by Michael Kirchhof, James Thornton, Kirchhof, Michael +9 · 3 citations
Engineering · Materials Science · Social Sciences · #Computational and Text Analysis Methods #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Nuclear Materials and Properties #Nuclear reactor physics and engineering
- Deep multi-class learning from label proportions
2019/05/30 by Dulac-Arnold, Gabriel, Zeghidour, Neil, Cuturi, Marco +2 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- On Fitting Flow Models with Large Sinkhorn Couplings
2025/06/05 by Stephen Zhang, Alireza Mousavi-Hosseini, Zhang, Stephen +5 · 2 voices · 5 citations
Computer Science · #Advanced Vision and Imaging #Generative Adversarial Networks and Image Synthesis #Medical Image Segmentation Techniques #cs.LG #stat.ML
- Debiased Sinkhorn barycenters
2020/06/03 by Hicham Janati, Marco Cuturi, Janati, Hicham +3 · 2 citations
Mathematics · Medicine · #Geometric Analysis and Curvature Flows #Advanced Neuroimaging Techniques and Applications
- Proximal Optimal Transport Modeling of Population Dynamics
2021/06/11 by Charlotte Bunne, Bunne, Charlotte, Laetitia Meng-Papaxanthos +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Diffusion and Search Dynamics #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks
- Debiaser Beware: Pitfalls of Centering Regularized Transport Maps
2022/02/17 by Pooladian, Aram-Alexandre, Cuturi, Marco, Niles-Weed, Jonathan · 1 citation
#FOS: Mathematics #Optimization and Control (math.OC) #Statistics Theory (math.ST)
- Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps
2023/02/08 by Marco Cuturi, Cuturi, Marco, Michal Klein +3 · 1 citation
Mathematics · #FOS: Biological sciences #FOS: Computer and information sciences #Genomics (q-bio.GN) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures
2025/03/13 by Nina Vesseron, Vesseron, Nina, Louis Béthune +3 · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques
- Tree-Sliced Variants of Wasserstein Distances
2019/02/01 by Tam Le, Le, Tam, Makoto Yamada +5 · 1 citation
Engineering · Environmental Science · #3D Shape Modeling and Analysis #Asphalt Pavement Performance Evaluation #FOS: Computer and information sciences #Groundwater flow and contamination studies #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Careful with that Scalpel: Improving Gradient Surgery with an EMA
2024/02/05 by Hsieh, Yu-Guan, Thornton, James, Ndiaye, Eugene +3 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Progressive Entropic Optimal Transport Solvers
2024/06/07 by Kassraie, Parnian, Pooladian, Aram-Alexandre, Klein, Michal +3 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
2023/10/21 by Lin, Tianyi, Cuturi, Marco, Jordan, Michael I. · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
- Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers
2024/12/23 by Manduchi, Laura, Wehenkel, Antoine, Behrmann, Jens +6 · 2 citations
#Biological Physics (physics.bio-ph) #Computational Engineering #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Machine Learning (cs.LG) #and Science (cs.CE)
- Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions
2024/07/09 by Yu-Guan Hsieh, Hsieh, Yu-Guan, Cheng-Yu Hsieh +17 · 1 citation
Computer Science · #Advanced Image and Video Retrieval Techniques #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Video Analysis and Summarization
- Learning Unmasking Policies for Diffusion Language Models
2025/12/09 by Metod Jazbec, Jazbec, Metod, Theo X. Olausson +14 · 2 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Topic Modeling
- The Data-Quality Illusion: Rethinking Classifier-Based Quality Filtering for LLM Pretraining
2025/10/01 by Saada, Thiziri Nait, Bethune, Louis, Klein, Michal +3 · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)