Graph Mixture Density Networks

Federico Errica
Federico Errica
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Abstract:

We introduce the Graph Mixture Density Network, a new family of machine learning models that can fit multimodal output distributions conditioned on arbitrary input graphs. By combining ideas from mixture models and graph representation learning, we address a broad class of challenging regression problems that rely on structured data. Ou...More

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