Optimal Interpolation Laws for Stable AR(1) Processes

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

Raphaël Huser, Emeric Rolland Georges Thibaud

Gaussian scale mixtures are constructed as Gaussian processes with a random variance. They have non-Gaussian marginals and can exhibit asymptotic dependence unlike Gaussian processes, which are asymptotically independent except in the case of perfect depen ...

Elsevier Sci Ltd2017

INTERNODES: an accurate interpolation-based method for coupling the Galerkin solutions of PDEs on subdomains featuring non-conforming interfaces

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We are interested in the approximation of partial differential equations on domains decomposed into two (or several) subdomains featuring non-conforming interfaces. The non-conformity may be due to different meshes and/or different polynomial degrees used ...

Elsevier2016

Spatial interpolation of experimental raindrop size distribution spectra

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We present a new approach for spatial interpolation of experimental raindrop size distribution (DSD) spectra. The DSD is fundamental to the study and understanding of precipitation and its monitoring and modelling. It is measured insitu using disdrometers ...

Wiley-Blackwell2016

An automated baseline correction protocol for infrared spectra of atmospheric aerosols collected on polytetrafluoroethylene (Teflon) filters

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A growing body of research on statistical applications for characterization of atmospheric aerosol Fourier transform infrared (FT-IR) samples collected on polytetrafluoroethylene (PTFE) filters (e.g., Russell et al., 2011; Ruthenburg et al., 2014) and a ri ...

European Geosciences Union2016

Statistical Optimality of Hermite Splines

Michaël Unser, Virginie Sophie Uhlmann, Julien René Pierre Fageot, Harshit Gupta

Hermite splines are commonly used for interpolating data when samples of the derivative are available, in a scheme called Hermite interpolation. Assuming a suitable statistical model, we demonstrate that this method is actually optimal for reconstructing r ...

IEEE2015

Adaptive Image Resizing Based on Continuous-Domain Stochastic Modeling

Michaël Unser, Aurélien Bourquard, Hagay Kirshner, John Paul Ward

We introduce an adaptive continuous-domain modeling approach to texture and natural images. The continuous-domain image is assumed to be a smooth function, and we embed it in a parameterized Sobolev space. We point out a link between Sobolev spaces and sto ...

Ieee-Inst Electrical Electronics Engineers Inc2014

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