Sliced Wasserstein distance between probability measures on Hilbert spaces
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Abstract (arXiv)
The sliced Wasserstein distance as well as its variants have been widely considered in comparing probability measures defined on mathbb Rd. Here we derive the notion of sliced Wasserstein distance for measures on an infinite dimensional separable Hilbert spaces, depict the relation between sliced Wasserstein distance and narrow convergence of measures and quantize the approximation via empirical measures.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jul 2023.
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Citing papers per year: 2024: 2; 2025: 3.
5 papers.
- 2025Mesh-Informed Neural Operator : A Transformer Generative Approachcited by 11
- 2024Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variatescited by 8
- 2025Slicing Wasserstein Over Wasserstein Via Functional Optimal Transportcited by 5
- 2024Max-sliced Wasserstein concentration and uniform ratio bounds of empirical measures on RKHScited by 1
- 2025Busemann Functions in the Wasserstein Space: Existence, Closed-Forms, and Applications to Slicingcited by 1
- 2025Busemann Functions in the Wasserstein Space: Existence, Closed-Forms, and Applications to Slicing6 Oct 2025
- 2025Slicing Wasserstein Over Wasserstein Via Functional Optimal Transport26 Sep 2025
- 2025Mesh-Informed Neural Operator : A Transformer Generative Approach20 Jun 2025
- 2024Max-sliced Wasserstein concentration and uniform ratio bounds of empirical measures on RKHS21 May 2024
- 2024Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates2 Feb 2024