Overview

Optimal transport studies how probability mass can be moved between distributions at minimum cost, giving a geometric way to compare data even when samples do not correspond one-to-one. Wasserstein distances and transport maps describe this geometry, while Gromov–Wasserstein methods compare relational structure when data live in different spaces. Practical approaches include entropic regularization with Sinkhorn algorithms, sliced and low-rank approximations, and neural transport maps used in generative modeling, domain adaptation, and trajectory inference. A central challenge is balancing computational and statistical scalability with faithful transport, especially when choosing regularization or relaxing exact mass constraints.

Latest papers

CardsList

291 papers50 papers in the last four weeks, up 22% on the four weeks before. 0.3% of all new papers.

  1. One Knob to Rule Them All: A Unified Optimal Transport View of Cold-Start Active Learning

    Aug 4, 2026Ning Zhu, Xiaochuan Ma, Juntao Xu +4Active LearningTraining Data Selection

  2. Computational and Statistical Guarantees of the c-Rectified flow

    Aug 3, 2026Leda Wang, Zhehao Xu, Qiang Liu +1Rectified FlowOptimal Transport

  3. Beckmann Transport Models: From Autonomous Flows to One-Step Maps

    Aug 3, 2026Lee Cheuk-Kit, Florentin Coeurdoux, Yuyuan Chen +5Flow MatchingOne-Step Generative Modeling

  4. Field Codes for Distributed Coupling Samplers and Certified Empirical Transport

    Jul 29, 2026Hung Mai, Hai Nguyen, Luong Doan +4Communication ComplexityOptimal Transport

  5. FPSGen: Flexible Point Cloud Scene Generation with BEV-Supported Transport Flows

    Jul 29, 2026Wenzhe He, Meng Wang, JiaWei Qian +3Point Cloud Completion3D Scene Generation

  6. UnDA: Unpaired Domain Alignment for Cross-Modal Knowledge Transfer in Medical Imaging

    Jul 23, 2026Rafsan Jany, Shadab Tanjeed Ahmad, Ahsan Bulbul +3Cross-Modal Knowledge DistillationCross-Modality Medical Image Segmentation

  7. OTAP: Structure-Aware Optimal Transport for Evaluating Planning and Execution in Agent Trajectories

    Jul 19, 2026Babak Barazandeh, Subhabrata Majumdar, George MichailidisLLM Agent EvaluationAI Agent Evaluation

  8. Twisted Schrödinger Bridge Matching

    Jul 18, 2026Maxence Noble, Marie Scheid, Yazid Janati +2Schrödinger BridgesTrajectory Inference

  9. Cluster-Aware Matching via Laplacian Optimal Transport

    Jul 17, 2026Gabriel Samberg, YoonHaeng Hur, Yuehaw Khoo +1ClusteringGraph Matching

  10. Fast Whole-Brain, Geometry-Aware Functional Alignment for Cross-Subject Decoding

    Jul 12, 2026Pierre-Louis Barbarant, Florent Meyniel, Bertrand ThirionNeural DecodingNeuroimaging

  11. Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering

    Jul 12, 2026Zhihao Yao, Yuxuan Gu, Jixuan Yin +1ClusteringUnsupervised Clustering

  12. Scalable Optimal Transport Algorithm for Network Alignment

    Jul 11, 2026Elaheh Hassani, Durga Mandarapu, Qi Yu +2Graph MatchingSparse Matrix Multiplication

  13. Control Laguerre Tessellation: Semi-discrete Optimal Transport Over Control Systems

    Jul 10, 2026Ripon C. Sarker, Abhishek HalderOptimal ControlOptimal Transport

  14. Wasserstein Residuals: Learning Gradient Flows from Population Dynamics

    Jul 6, 2026Markus Heinonen, Yair Shenfeld, Ricardo Baptista +4Dynamical SystemsWasserstein Gradient Flows

  15. The Fundamental Limits of Valid Transport Map Estimation

    Jun 29, 2026Sivaraman BalakrishnanMinimax EstimationGenerative Modeling

  16. ITSPACE: Monotone Gaussian Optimal Transport Updates

    Jun 29, 2026Woojoo Na, Jennifer DyMatrix OptimizationOptimal Transport

  17. Highly Data Parallelizable Estimation of the Sliced-Wasserstein Distance Using Cumulative Distribution Functions

    Jun 29, 2026Christophe Vauthier, Quentin Mérigot, Anna KorbaSliced Wasserstein DistanceOptimal Transport

  18. MIRROR: Aligning Semantic Relations from Language to Image via Gromov--Wasserstein

    Jun 28, 2026Hong-Han Wang, Yuntao Wang, Hu DingLarge Vision-Language ModelsVLM Reasoning

  19. Difference of Convex Programming in the Wasserstein Space with Applications to MMD Optimization

    Jun 26, 2026Clément Bonet, Pierre-Cyril Aubin-Frankowski, Youssef MrouehMaximum Mean DiscrepancyNonconvex Optimization

  20. Bridging Vision and Language Concepts through Optimal Transport Semantic Flow

    Jun 25, 2026Chenyang Zhang, Anqi Dong, Guangming Zhu +4Concept Bottleneck ModelsVLM Interpretability

  21. Variational Inference via Entropic Transport Descent

    Jun 24, 2026Vincent Pacelli, Akash Ratheesh, Evangelos TheodorouBayesian InferenceVariational Inference

  22. Counting Trees from Satellite Imagery with Noisy Supervision

    Jun 23, 2026Dimitri Gominski, Maurice Mugabowindekwe, Qiue Xu +6Remote SensingLearning with Noisy Labels

  23. Sample complexity of unbalanced entropic OT

    Jun 23, 2026Francisco Andrade, Gabriel Peyré, Clarice PoonSample ComplexityEntropy Regularization

  24. A Transport-Based Geometry of Belief-Cost

    Jun 19, 2026Laurent CaraffaInformation GeometryOptimal Transport

  25. Intrinsic Flow Matching on Quantum Pure-State Manifolds with Phase-Aligned Transport

    Jun 19, 2026Jian Xu, Delu Zeng, John Paisley +1Flow MatchingQuantum Generative Modeling

  26. OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classification

    Jun 18, 2026Jiwoong Yang, Haejun Chung, Ikbeom JangMulti-View ConsistencyMulti-View Learning