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DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
Regression with non-Euclidean responses---e.g., probability distributions, networks, symmetric positive-definite matrices, and compositions---has become increasingly important in modern applications. In this paper, we propose deep Fréchet neural networks (DFNNs), an end-to-end deep learning framewor
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