{"total":35,"rows":[{"id":"2103.04737","title":"Low-Rank Sinkhorn Factorization","created":"2021-03-08","cited_by_count":67,"area":null},{"id":"2306.16156","title":"Recent Advances in Optimal Transport for Machine Learning","created":"2023-06-28","cited_by_count":66,"area":null},{"id":"2206.14262","title":"Supervised Training of Conditional Monge Maps","created":"2022-06-28","cited_by_count":61,"area":null},{"id":"2102.06555","title":"Online Graph Dictionary Learning","created":"2021-02-12","cited_by_count":37,"area":null},{"id":"2205.06688","title":"A Unified Framework for Implicit Sinkhorn Differentiation","created":"2022-05-13","cited_by_count":28,"area":null},{"id":"2209.13570","title":"Hierarchical Sliced Wasserstein Distance","created":"2022-09-27","cited_by_count":23,"area":null},{"id":"2110.02753","title":"Semi-relaxed Gromov-Wasserstein divergence with applications on graphs","created":"2021-10-06","cited_by_count":21,"area":null},{"id":"2205.12365","title":"Low-rank Optimal Transport: Approximation, Statistics and Debiasing","created":"2022-05-24","cited_by_count":21,"area":null},{"id":"2110.02887","title":"Using Optimal Transport as Alignment Objective for fine-tuning Multilingual Contextualized Embeddings","created":"2021-10-06","cited_by_count":19,"area":null},{"id":"2211.03329","title":"Implicit Graphon Neural Representation","created":"2022-11-07","cited_by_count":19,"area":null},{"id":"2305.04034","title":"Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transport","created":"2023-05-06","cited_by_count":16,"area":null},{"id":"2305.16557","title":"Tree-Based Diffusion Schr\\\"odinger Bridge with Applications to Wasserstein Barycenters","created":"2023-05-26","cited_by_count":16,"area":null},{"id":"2206.07630","title":"Rethinking Initialization of the Sinkhorn Algorithm","created":"2022-06-15","cited_by_count":14,"area":null},{"id":"2307.14953","title":"Multi-Source Domain Adaptation through Dataset Dictionary Learning in Wasserstein Space","created":"2023-07-27","cited_by_count":12,"area":null},{"id":"2201.12195","title":"Measure Estimation in the Barycentric Coding Model","created":"2022-01-28","cited_by_count":9,"area":null},{"id":"2206.03230","title":"Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances","created":"2022-06-07","cited_by_count":7,"area":null},{"id":"2102.12178","title":"Learning to Generate Wasserstein Barycenters","created":"2021-02-24","cited_by_count":6,"area":null},{"id":"2404.10261","title":"Lighter, Better, Faster Multi-Source Domain Adaptation with Gaussian Mixture Models and Optimal Transport","created":"2024-04-16","cited_by_count":5,"area":null},{"id":"2111.00043","title":"Multivariate rank via entropic optimal transport: sample efficiency and generative modeling","created":"2021-10-29","cited_by_count":4,"area":null},{"id":"2304.14852","title":"Wasserstein Dictionaries of Persistence Diagrams","created":"2023-04-28","cited_by_count":4,"area":null},{"id":"2601.09974","title":"SPRInG: Continual LLM Personalization via Selective Parametric Adaptation and Retrieval-Interpolated Generation","created":"2026-01-15","cited_by_count":4,"area":null},{"id":"2203.12136","title":"Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters","created":"2022-03-23","cited_by_count":3,"area":null},{"id":"2210.12135","title":"Geometric Sparse Coding in Wasserstein Space","created":"2022-10-21","cited_by_count":3,"area":null},{"id":"2104.01708","title":"A unified framework for non-negative matrix and tensor factorisations with a smoothed Wasserstein loss","created":"2021-04-04","cited_by_count":2,"area":null},{"id":"2306.07996","title":"Point spread function modelling for astronomical telescopes: a review focused on weak gravitational lensing studies","created":"2023-06-12","cited_by_count":1,"area":null},{"id":"2407.11647","title":"Dataset Dictionary Learning in a Wasserstein Space for Federated Domain Adaptation","created":"2024-07-16","cited_by_count":1,"area":null},{"id":"2410.23602","title":"Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications","created":"2024-10-31","cited_by_count":1,"area":null},{"id":"2505.11913","title":"Joint Manifold Learning and Optimal Transport for Dynamic Imaging","created":"2025-05-17","cited_by_count":1,"area":null},{"id":"2603.26940","title":"Static and Dynamic Approaches to Computing Barycenters of Probability Measures on Graphs","created":"2026-03-27","cited_by_count":1,"area":null},{"id":"2103.09085","title":"Exact Sparse Orthogonal Dictionary Learning","created":"2021-03-14","cited_by_count":0,"area":null},{"id":"2306.10505","title":"Structure-Sensitive Graph Dictionary Embedding for Graph Classification","created":"2023-06-18","cited_by_count":0,"area":null},{"id":"2507.11719","title":"Barycentric model aggregation in the Wasserstein space of distributions and a variational approach to consistency","created":"2025-07-15","cited_by_count":0,"area":null},{"id":"2603.10132","title":"Unbalanced Optimal Transport Dictionary Learning for Unsupervised Hyperspectral Image Clustering","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2605.18276","title":"Geometric Dictionary Learning of Dynamical Systems with Optimal Transport","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2610.04091","title":"Robust blind unmixing: A geometric approach to overcoming basis variation","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}