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Distributional Regression for Arbitrary Response Variables Using ReLU Neural Networks
This paper develops a unified framework for distributional regression with arbitrary response variables. Rather than relying on scalar thresholds or Euclidean structure, we model conditional event probabilities indexed by measurable sets, which extends distributional regression to general response s
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