Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures

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Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures

Chattez avec Graph Search

Flexible Statistical Inference for Multivariate Extremes

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Holography and localization of information in quantum gravity

Technosignatures Longevity and Lindy's Law

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Robust discrete choice models with t-distributed kernel errors

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

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Regularization for distributionally robust state estimation and prediction

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Distributionally Robust Linear Quadratic Control

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Data-driven modeling of beam loss in the LHC

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The elliptical Ornstein-Uhlenbeck process

Towards a multiscale point cloud structural similarity metric