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Publications associées (34)

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Modern digital connectivity has necessitated the creation of robust methods for securely storing and transferring data. At the heart of all security infrastructure is the random number generator (RNG). While random numbers find use in a variety of applicat ...

EPFL2023

An animals' ability to learn how to make decisions based on sensory evidence is often well described by Reinforcement Learning (RL) frameworks. These frameworks, however, typically apply to event-based representations and lack the explicit and fine-grained ...

2021

We establish probabilistic small data global well-posedness of the energy-critical Maxwell-Klein-Gordon equation relative to the Coulomb gauge for scaling super-critical random initial data. The proof relies on an induction on frequency procedure and a mod ...

2020

Max-infinitely divisible models and inference for spatial extremes

Emeric Rolland Georges Thibaud, Raphaël Huser

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable models are inadequate to capture the rate of joint tail decay, and to estimate jo ...

WILEY2020

Multivariate extremes over a random number of observations

Simone Padoan, Stefano Rizzelli

The classical multivariate extreme-value theory concerns the modeling of extremes in a multivariate random sample, suggesting the use of max-stable distributions. In this work, the classical theory is extended to the case where aggregated data, such as max ...

WILEY2020

Ventricular response regularity in atrial fibrillation and its relationship to successful catheter ablation

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

Atrial rate is known to modulate ventricular response during atrial fibrillation (AF). The resulting pulse irregularity translates into widely varying inter-beat intervals (IBIs) extracted from recorded surface electrocardiogram (ECG) activity. In AF, the ...

IEEE2020

Statistical comparison of the performance of data-based models for sewer condition modeling

José Pedro Gamito de Saldanha Calado Matos

The present article proposes a methodology to consider the uncertainty intrinsic to data-based models when comparing their performance. The goal is to provide a quantification of the variability of this type of models due to the random nature of the calibr ...

2019

Asynchronous adaptive networks

Ali H. Sayed

In a recent article [1] we surveyed advances related to adaptation, learning, and optimization over synchronous networks. Various distributed strategies were discussed that enable a collection of networked agents to interact locally in response to streamin ...

Elsevier2018

A methodology for the rigorous verification of Particle-in-Cell simulations

Paolo Ricci, Fabio Riva, Carrie Fiona Beadle

A methodology to perform a rigorous verification of Particle-in-Cell (PIC) simulations is presented, both for assessing the correct implementation of the model equations (code verification), and evaluating the numerical uncertainty affecting the simulation ...

American Institute of Physics2017

A methodology for the rigorous verification of plasma simulation codes

Paolo Ricci, Joaquim Loizu Cisquella, Paola Paruta, Sébastien Jolliet, Federico David Halpern, Fabio Riva, Annamaria Mosetto, Christoph Wersal, Carrie Fiona Beadle

2017