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Publications associées (28)

Contributions to Likelihood-Based Modelling of Extreme Values

Léo Raymond-Belzile

xtreme value analysis is concerned with the modelling of extreme events such as floods and heatwaves, which can have large impacts. Statistical modelling can be useful to better assess risks even if, due to scarcity of measurements, there is inherently ver ...

EPFL2019

Feasibility of Time Synchronization Attacks against PMU-based State-Estimation

Jean-Yves Le Boudec, Mario Paolone, Sergio Barreto Andrade, Marguerite Marie Nathalie Delcourt, Gyorgy Miklos Dan

The emerging measurement technology of phasor measurement units (PMUs) makes it possible to estimate the state of electrical grids in real-time, thus opening the way to new protection and control applications. PMUs rely on precise time synchronization, the ...

2019

Modeling Dielectric Constant Variability in Aggregate Polymers from CV Measurements

Marco Mattavelli, Jean-Michel Sallese, Catherine Dehollain, Diego Ruben Barrettino

Recently a new technique based on capacitive sensing has been developed and used to estimate the amount of moisture in polymers by means of the deviation of the dielectric constant. This technique is expected to be used for in-line monitoring of aggregate ...

IEEE2019

Statistical inference in ensemble modeling of cellular metabolism

Vassily Hatzimanikatis, Marc-Olivier Boldi, Tuure Eelis Hameri

Kinetic models of metabolism can be constructed to predict cellular regulation and devise metabolic engineering strategies, and various promising computational workflows have been developed in recent years for this. Due to the uncertainty in the kinetic pa ...

2019

Gaussian Process Regression for Maximum Entropy Distribution

Mohsen Sadr

Maximum-Entropy Distributions offer an attractive family of probability densities suitable for moment closure problems. Yet finding the Lagrange multipliers which parametrize these distributions, turns out to be a computational bottleneck for practical clo ...

2019

Sequential Outlier Detection Based on Incremental Decision Trees

Hakan Gökcesu, Kaan Gökcesu

We introduce an online outlier detection algorithm to detect outliers in a sequentially observed data stream. For this purpose, we use a two-stage filtering and hedging approach. In the first stage, we construct a multimodal probability density function to ...

2019

Modelling the Syntax of North Indian Melodies with a Generalized Graph Grammar

Martin Alois Rohrmeier, Christoph Finkensiep

Hierarchical models of music allow explanation of highly complex musical structure based on the general principle of recursive elaboration and a small set of orthogonal operations. Recent approaches to melodic elaboration have converged to a representation ...

ISMIR2019

A Bayesian Approach To Inter-Task Fusion For Speaker Recognition

Petr Motlicek, Subhadeep Dey

In i-vector based speaker recognition systems, back-end classifiers are trained to factor out nuisance information and retain only the speaker identity. As a result, variabilities arising due to gender, language and accent ( among many others) are suppress ...

IEEE2019

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