Residual-based conditional variance estimation with dense ReLU networks achieves non-asymptotic rates under sub-Exponential noise, and a bootstrap interval for the conditional mean is proven to have coverage at least 1-alpha.
Adaptive variance function estimation in heteroscedastic nonparametric regression
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Confidence Interval Construction and Conditional Variance Estimation with Dense ReLU Networks
Residual-based conditional variance estimation with dense ReLU networks achieves non-asymptotic rates under sub-Exponential noise, and a bootstrap interval for the conditional mean is proven to have coverage at least 1-alpha.