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Federica Zoe Ricci

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#machine learning Preprint Oct 2026

xVGAE: A Hierarchical Variational Graph Autoencoder for Exchangeable Graphs

Graphs play a crucial role in many applications, ranging from drug discovery to social network modeling and astronomy. Generative models for graphs have substantially advanced in recent years, but we identify relatively simple scenarios where state-of-the-art models struggle to converge within a standard compute budget...

D. Micheletti, Federica Zoe Ricci, Erik B. Sudderth · 0 citations

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