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Publications associées (23)

Multivalent Pattern Recognition Through Engineering of Spatial Tolerance in DNA-Based Nanomaterials

Strength in numbers, combining many weak interactions into an overall strong connection, is the fundamental principle of multivaleny. This concept has been exploiting for the engineering of super-selective cell-targeting materials, which generally display ...

EPFL2022

Superluminal Motion-Assisted Four-Dimensional Light-in-Flight Imaging

Edoardo Charbon, Andrei Ardelean, Ming-Lo Wu, Kazuhiro Morimoto

Advances in high-speed imaging techniques have opened new possibilities for capturing ultrafast phenomena such as light propagation in air or through media. Capturing light in flight in three-dimensional xyt space has been reported based on various types o ...

AMER PHYSICAL SOC2021

Probabilistic Deep Learning on Spheres for Weather/Climate Applications

This work presents the application of a probabilistic approach to an already existing deep learning model for weather and climate prediction. Probabilistic deep learning allows to capture and address the uncertainties related to the data given as input and ...

2020

Spatial covariance improves BCI performance for late ERPs components with high temporal variability

Ricardo Andres Chavarriaga Lozano, Lucian Andrei Gheorghe, Marija Uscumlic, Ruslan Aydarkhanov

Objective. Event Related Potentials (ERPs) reflecting cognitive response to external stimuli, are widely used in brain computer interfaces. ERP waveforms are characterized by a series of components of particular latency and amplitude. The classical ERP dec ...

2020

High-Frequency Analysis Of Parabolic Stochastic Pdes

Carsten Hao Ye Chong

We consider the problem of estimating stochastic volatility for a class of second-order parabolic stochastic PDEs. Assuming that the solution is observed at high temporal frequency, we use limit theorems for multipower variations and related functionals to ...

INST MATHEMATICAL STATISTICS2020

Spatial interpolation of precipitation from multiple rain gauge networks and weather radar data for operational applications in Alpine catchments

Giovanni De Cesare, Javier García Hernández, Bettina Schaefli, Alain Tommy Foehn

Increasing meteorological data availability and quality implies an adaptation of the interpolation methods for data combination. In this paper, we propose a new method to efficiently combine weather radar data with data from two heated rain gauge networks ...

2018

2D ultrasonic flow mapping of the secondary flow field in free-surface vortices

Giovanni De Cesare

In this study, an application of two dimensional ultrasonic doppler flow mapping was undertaken on a strong full air core free-surface vortex. The vortex was generated in a scroll type vortex chamber with a subcritical approach flow which have common appli ...

2018

Geostatistical modelling for the monitoring of environmental-related endemic diseases: Application to the distribution of schistosomiasis in Burkina Faso

Laurent Hafiz

The increased interest of reducing the infection rates of neglected tropical diseases like schistosomiasis in the world has raised the necessity of developing epidemiological monitoring techniques, in order to target specific areas where the risk of infect ...

2014

Geostatistics of Dependent and Asymptotically Independent Extremes

Anthony Christopher Davison, Emeric Rolland Georges Thibaud, Raphaël Huser

Spatial modeling of rare events has obvious applications in the environmental sciences and is crucial when assessing the effects of catastrophic events (such as heatwaves or widespread flooding) on food security and on the sustainability of societal infras ...

Springer Heidelberg2013

Geostatistics of extremes

Anthony Christopher Davison

We describe a prototype approach to flexible modelling for maxima observed at sites in a spatial domain, based on fitting of max-stable processes derived from underlying Gaussian random fields. The models we propose have generalised extreme-value marginal ...

2012

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