AINeutralarXiv – CS AI · 7h ago6/10
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End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
Researchers introduce E2M (End-to-End Metric regression), a deep learning framework that predicts non-Euclidean outputs like probability distributions and networks by computing weighted Fréchet means with neural network-learned weights. The method preserves geometric properties of output spaces while achieving state-of-the-art performance across multiple domains without requiring surrogate embeddings.