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Differentiable Generalized Sliced Wasserstein Plans

arXiv — cs.LG•Tuesday, November 4, 2025 at 5:00:00 AM
PositiveArtificial Intelligence

Differentiable Generalized Sliced Wasserstein Plans

A new approach in optimal transport, known as min-SWGG, is making waves in the machine learning community. This innovative slicing technique aims to tackle the computational challenges associated with large datasets, enhancing the efficiency of defining distances between probability distributions. As researchers continue to explore the potential of optimal transport, advancements like min-SWGG could significantly improve data analysis and modeling, making it easier for practitioners to work with complex datasets.
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