A unified framework is introduced for finite element and box discretizations of fractional powers of elliptic operators, where mass lumping produces the intrinsic fractional box method and error estimates are derived under consistency assumptions.
Journal of Multivariate Analysis , volume=
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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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Finite element and box-method discretizations for fractional elliptic problems with quadrature and mass lumping
A unified framework is introduced for finite element and box discretizations of fractional powers of elliptic operators, where mass lumping produces the intrinsic fractional box method and error estimates are derived under consistency assumptions.
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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.