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Gabriel Melo

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#machine learning Preprint Sep 2026

Graph Matching Relaxations and Amortization for Supervised Graph Prediction

This work proposes to amortize the graph matching (node alignment) problem and showcases the efficiency of this approach on toy and real world SGP problems of increasing complexity including a novel Mass-spectra to Scaffold task that is introduced.

F. Méndez, Paul Krzakala, Gabriel Melo et al. · 0 citations

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