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Accurate solution of Bayesian inverse uncertainty quantification problems combining reduced basis methods and reduction error models

Andrea Manzoni, Toni Mikael Lassila, Stefano Pagani
2016
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Andrea Manzoni, Toni Mikael Lassila, Stefano Pagani
2016
Journal Articles

Official source

Related publications (3)

https://infoscience.epfl.ch/entities/publication/c7f7b2f6-dd8c-4ee3-b2e6-30907b9155bb

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Related publications (3)

The Structure of Free Polyphony

Christoph Finkensiep

The human ability to perceive and understand music is remarkable. From an unstructured stream of acoustic input it creates a wide range of experiences, from psycho-acoustic effects to emotional and aesthetic responses. One such set of phenomena is the expe ...

EPFL2023

SUIHTER: a new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy

Alfio Quarteroni

The COVID-19 epidemic is the latest in a long list of pandemics that have affected humankind in the last century. In this paper, we propose a novel mathematical epidemiological model named SUIHTER from the names of the seven compartments that it comprises: ...

ROYAL SOC2021

A Novel Bayesian Impulse Radio Ultra-WideBand Ranging Algorithm

Jean-Yves Le Boudec

We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under weak Line Of Sight (LOS) environments and additive Gaussian noise. We use a Bayesian approach where the prior distribution of the channel follows the IEEE 802.15.4a ...

IEEE2009