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Author

Andrew Warren

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Preprint Aug 2026

Beyond Procrustes distances: a multilinear Gromov-Wasserstein distance capturing chirality

Efficiently and robustly analyzing shape data is critical across many scientific disciplines. While chirality is a fundamental property in numerous applications - most notably in molecular science - existing shape analysis metrics fail to distinguish between a shape and its mirror image. To address this gap, we introdu...

Clément Soubrier, Geoffrey Woollard, Andrew Warren et al. · 0 citations
#machine learning Preprint Aug 2026

Beyond Procrustes distances: a multilinear Gromov-Wasserstein distance capturing chirality

Efficiently and robustly analyzing shape data is critical across many scientific disciplines. While chirality is a fundamental property in numerous applications - most notably in molecular science - existing shape analysis metrics fail to distinguish between a shape and its mirror image. To address this gap, we introdu...

Clément Soubrier, Geoffrey Woollard, Andrew Warren et al. · 0 citations

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