AI RESEARCH
Sliced Inner Product Gromov-Wasserstein Distances
arXiv CS.LG
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ArXi:2605.08546v1 Announce Type: cross The Gromo-Wasserstein (GW) problem provides a framework for aligning heterogeneous datasets by matching their intrinsic geometry, but its statistical and computational scaling remains an issue for high-dimensional problems. Slicing techniques offer an appealing route to scalability, but, unlike Wasserstein distances, GW problems do not generally admit closed-form solutions in one-dimension.