AI RESEARCH
Fused Gromov-Wasserstein Distance with Feature Selection
arXiv CS.LG
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ArXi:2605.12161v1 Announce Type: new Fused Gromo-Wasserstein (FGW) distances provide a principled framework for comparing objects by jointly aligning structure and node features. However, existing FGW formulations treat all features uniformly, which limits interpretability and robustness in high-dimensional settings where many features may be irrelevant or noisy. We