Quantile total variation denoising admits an exact minmax characterization of its fitted values as compact intervals whose endpoints are given by minmax functionals of local order statistics.
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A random scale mixture process with amortized Bayesian inference enables scalable modeling of spatially dependent extreme temperatures and associated heat risks.
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An Exact Pointwise Characterization for Total Variation Denoising in Quantile Regression
Quantile total variation denoising admits an exact minmax characterization of its fitted values as compact intervals whose endpoints are given by minmax functionals of local order statistics.
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Spatial Extremes at Scale: A Case Study of Surface Skin Temperature and Heat Risk in the United States
A random scale mixture process with amortized Bayesian inference enables scalable modeling of spatially dependent extreme temperatures and associated heat risks.