{"total":64,"rows":[{"id":"2103.03606","title":"Unbalanced minibatch Optimal Transport; applications to Domain Adaptation","created":"2021-03-05","cited_by_count":125,"area":null},{"id":"2101.01792","title":"Minibatch optimal transport distances; analysis and applications","created":"2021-01-05","cited_by_count":65,"area":null},{"id":"2102.04014","title":"Point-set Distances for Learning Representations of 3D Point Clouds","created":"2021-02-08","cited_by_count":48,"area":null},{"id":"2108.09645","title":"Improving Mini-batch Optimal Transport via Partial Transportation","created":"2021-08-22","cited_by_count":41,"area":null},{"id":"2106.15427","title":"Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections","created":"2021-06-29","cited_by_count":33,"area":null},{"id":"2402.18377","title":"Out-of-Domain Generalization in Dynamical Systems Reconstruction","created":"2024-02-28","cited_by_count":33,"area":null},{"id":"2404.18962","title":"An Aggregation-Free Federated Learning for Tackling Data Heterogeneity","created":"2024-04-29","cited_by_count":33,"area":null},{"id":"2206.05262","title":"Meta Optimal Transport","created":"2022-06-10","cited_by_count":28,"area":null},{"id":"2305.05080","title":"Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey","created":"2023-05-08","cited_by_count":27,"area":null},{"id":"2209.00517","title":"The Neural Process Family: Survey, Applications and Perspectives","created":"2022-09-01","cited_by_count":23,"area":null},{"id":"2212.08049","title":"Sliced Optimal Partial Transport","created":"2022-12-15","cited_by_count":20,"area":null},{"id":"2303.05798","title":"Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals","created":"2023-03-10","cited_by_count":19,"area":null},{"id":"2102.12833","title":"Diffusion Earth Mover's Distance and Distribution Embeddings","created":"2021-02-25","cited_by_count":18,"area":null},{"id":"2202.03926","title":"Distribution Regression with Sliced Wasserstein Kernels","created":"2022-02-08","cited_by_count":18,"area":null},{"id":"2107.09539","title":"Parametric Scattering Networks","created":"2021-07-20","cited_by_count":16,"area":null},{"id":"2307.02402","title":"Unbalanced Optimal Transport: A Unified Framework for Object Detection","created":"2023-07-05","cited_by_count":15,"area":null},{"id":"2208.09932","title":"Improving GANs for Long-Tailed Data through Group Spectral Regularization","created":"2022-08-21","cited_by_count":14,"area":null},{"id":"2108.10961","title":"Entropic Gromov-Wasserstein between Gaussian Distributions","created":"2021-08-24","cited_by_count":12,"area":null},{"id":"2105.14403","title":"Re-evaluating Word Mover's Distance","created":"2021-05-30","cited_by_count":10,"area":null},{"id":"2502.07962","title":"ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans","created":"2025-02-11","cited_by_count":10,"area":null},{"id":"2106.02146","title":"The Signed Cumulative Distribution Transform for 1-D Signal Analysis and Classification","created":"2021-06-03","cited_by_count":9,"area":null},{"id":"2112.05872","title":"SLOSH: Set LOcality Sensitive Hashing via Sliced-Wasserstein Embeddings","created":"2021-12-11","cited_by_count":9,"area":null},{"id":"2206.12116","title":"Approximating 1-Wasserstein Distance with Trees","created":"2022-06-24","cited_by_count":9,"area":null},{"id":"2207.04613","title":"Nonlinear Sufficient Dimension Reduction for Distribution-on-Distribution Regression","created":"2022-07-11","cited_by_count":8,"area":null},{"id":"2402.01493","title":"Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates","created":"2024-02-02","cited_by_count":8,"area":null},{"id":"2110.10524","title":"Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences","created":"2021-10-20","cited_by_count":7,"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":"2310.13653","title":"Optimal Transport for Measures with Noisy Tree Metric","created":"2023-10-20","cited_by_count":7,"area":null},{"id":"2402.03838","title":"Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels","created":"2024-02-06","cited_by_count":7,"area":null},{"id":"2210.06574","title":"Gaussian Processes on Distributions based on Regularized Optimal Transport","created":"2022-10-12","cited_by_count":6,"area":null},{"id":"2212.00133","title":"Universal Neural Optimal Transport","created":"2022-11-30","cited_by_count":6,"area":null},{"id":"2311.00927","title":"Scalable Counterfactual Distribution Estimation in Multivariate Causal Models","created":"2023-11-02","cited_by_count":6,"area":null},{"id":"2203.02227","title":"Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration","created":"2022-03-04","cited_by_count":5,"area":null},{"id":"2104.07232","title":"Iterative Alignment Flows","created":"2021-04-15","cited_by_count":4,"area":null},{"id":"2302.03663","title":"SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics","created":"2023-02-07","cited_by_count":4,"area":null},{"id":"2405.17164","title":"WeiPer: OOD Detection using Weight Perturbations of Class Projections","created":"2024-05-27","cited_by_count":4,"area":null},{"id":"2503.13756","title":"Fast rigid alignment of heterogeneous images in sliced Wasserstein distance","created":"2025-03-17","cited_by_count":4,"area":null},{"id":"2408.00549","title":"Learning to Embed Distributions via Maximum Kernel Entropy","created":"2024-08-01","cited_by_count":3,"area":null},{"id":"2202.08532","title":"Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition","created":"2022-02-17","cited_by_count":2,"area":null},{"id":"2307.13571","title":"PT$\\mathrm{L}^{p}$: Partial Transport $\\mathrm{L}^{p}$ Distances","created":"2023-07-25","cited_by_count":2,"area":null},{"id":"2309.15787","title":"Partial Transport for Point-Cloud Registration","created":"2023-09-27","cited_by_count":2,"area":null},{"id":"2506.02203","title":"Constrained Sliced Wasserstein Embedding","created":"2025-06-02","cited_by_count":2,"area":null},{"id":"2604.07925","title":"Sinkhorn doubly stochastic attention rank decay analysis","created":"2026-04-09","cited_by_count":2,"area":null},{"id":"2106.05739","title":"Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics","created":"2021-06-10","cited_by_count":1,"area":null},{"id":"2109.03378","title":"Rethinking Multidimensional Discriminator Output for Generative Adversarial Networks","created":"2021-09-08","cited_by_count":1,"area":null},{"id":"2210.13630","title":"Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport","created":"2022-10-24","cited_by_count":1,"area":null},{"id":"2308.14335","title":"Improved learning theory for kernel distribution regression with two-stage sampling","created":"2023-08-28","cited_by_count":1,"area":null},{"id":"2402.00580","title":"Continuous Unsupervised Domain Adaptation Using Stabilized Representations and Experience Replay","created":"2024-01-31","cited_by_count":1,"area":null},{"id":"2411.07432","title":"Fast unsupervised ground metric learning with tree-Wasserstein distance","created":"2024-11-11","cited_by_count":1,"area":null},{"id":"2502.05435","title":"Unbiased Sliced Wasserstein Kernels for High-Quality Audio Captioning","created":"2025-02-08","cited_by_count":1,"area":null},{"id":"2505.14128","title":"A Methodological Framework for Measuring Spatial Labeling Similarity","created":"2025-05-20","cited_by_count":1,"area":null},{"id":"2509.10166","title":"Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance","created":"2025-09-12","cited_by_count":1,"area":null},{"id":"2511.02848","title":"EEGReXferNet: A Lightweight Gen-AI Framework for EEG Subspace Reconstruction via Cross-Subject Transfer Learning and Channel-Aware Embedding","created":"2025-10-26","cited_by_count":1,"area":null},{"id":"2112.01878","title":"Fast $L^2$ optimal mass transport via reduced basis methods for the Monge-Amp$\\grave{\\rm e}$re equation","created":"2021-12-03","cited_by_count":0,"area":null},{"id":"2310.10143","title":"An Empirical Study of Self-supervised Learning with Wasserstein Distance","created":"2023-10-16","cited_by_count":0,"area":null},{"id":"2310.18586","title":"Optimal Transport for Kernel Gaussian Mixture Models","created":"2023-10-28","cited_by_count":0,"area":null},{"id":"2401.01035","title":"Online Continual Domain Adaptation for Semantic Image Segmentation Using Internal Representations","created":"2024-01-02","cited_by_count":0,"area":null},{"id":"2404.03273","title":"Gaussian-Smoothed Sliced Probability Divergences","created":"2024-04-04","cited_by_count":0,"area":null},{"id":"2505.17204","title":"Liouville PDE-based sliced-Wasserstein flow","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2507.13194","title":"Relation-Aware Slicing in Cross-Domain Alignment","created":"2025-07-17","cited_by_count":0,"area":null},{"id":"2601.13191","title":"Empirical Risk Minimization with $f$-Divergence Regularization","created":"2026-01-19","cited_by_count":0,"area":null},{"id":"2602.06539","title":"Revisiting the Sliced Wasserstein Kernel for persistence diagrams: a Figalli-Gigli approach","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2605.04873","title":"Measuring Psychological States Through Semantic Projection: A Theory-Driven Approach to Language-Based Assessment","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2607.20119","title":"Directional Kernel Mean Difference: A Fast Signed Statistic for Univariate Distribution Comparison","created":"2026-07-22","cited_by_count":0,"area":null}],"next_cursor":null}