Web1 de dez. de 2024 · Instead of using sliced Wasserstein distance, existing hierarchical optimal transport models apply Wasserstein distance [8,42,38] or entropic Wasserstein distance [21] to calculate the cost matrix C. WebIn many machine learning applications, it is necessary to meaningfully aggregate, through alignment, different but related datasets. Optimal transport (OT)-based approaches pose alignment as a divergence minimization problem: the aim is to transform a source dataset to match a target dataset using the Wasserstein distance as a divergence measure …
Hierarchical Optimal Transport for Multimodal Distribution …
WebWe introduce a hierarchical formulation of\nOT for clustered and multi-subspace datasets called Hierarchical Wasserstein Alignment (HiWA)3.\nWe empirically show that when data are well approximated with Gaussian mixture models (GMMs)\nor lie on a union of subspaces, we may leverage existing clustering pipelines (e.g., sparse … Web27 de jun. de 2024 · In many machine learning applications, it is necessary to meaningfully aggregate, through alignment, different but related datasets. Optimal transport (OT) … how did christianity grow in the roman empire
Proceedings of Machine Learning Research
WebHierarchical Wasserstein Alignment (HiWA) This toolbox contains MATLAB code associated with the Neurips 2024 paper titled Hierarchical Optimal Transport for Multimodal Distribution Alignment. The python … WebUnsupervised Multilingual Alignment using Wasserstein Barycenter by Xin Lian A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of ... 3.3 Hierarchical Approach .....38 4 Experiments 41 5 Conclusion and Discussion 53 6 References 55 vii. List of Figures 1 ... Web28 de nov. de 2024 · Hierarchical Wasserstein alignment 43 improves on this strategy by leveraging the tendency of neural circuits to constrain their low-dimensional activity to clusters or multiple low-dimensional ... how did christianity influence architecture