Related publications (5)

Improved modelling of a monomorph piezoelectric actuator for linear self-sensing applications

Yves Perriard, Louis Antoine Masson

Based on a previous approach for the modelling of piezoelectric monomorph benders, a new, more complete, analytical model is proposed. Some previously neglected features of the actuator stack, notably the thickness of the electrodes and the presence of iso ...
IEEE2019

Likelihood estimators for multivariate extremes

Anthony Christopher Davison, Raphaël Huser

The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high t ...
Springer2016

Mapping extreme snowfalls in the French Alps using max-stable processes

Johan Alexandre Philippe Gaume

The evaluation of extreme snowfalls is an important challenge for hazard management in mountainous regions. In this paper, the extreme snowfall data acquired from 40 meteorological stations in the French Alps since 1966 are analyzed using spatial extreme s ...
2013

Learning with Compressible Priors

Volkan Cevher

We describe a set of probability distributions, dubbed compressible priors, whose independent and identically distributed (iid) realizations result in p-compressible signals. A signal x in R^N is called p-compressible with magnitude R if its sorted coeffic ...
2009

Mixture models for multivariate extremes

Marc-Olivier Boldi

This thesis is a contribution to multivariate extreme value statistics. The tail of a multivariate distribution function is characterized by its spectral distribution, for which we propose a new semi-parametric model based on mixtures of Dirichlet distribu ...
EPFL2004

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