Publications associées à Moyenne mobile

Directional sensitivity of cortical neurons towards TMS induced electric fields

Werner Alfons Hilda Van Geit, Aurélien Tristan Jaquier

We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 24 ...

2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Benjamin Bejar Haro, Ekaterina Krymova, Ntorina Thanou, Nicola Parolini, Daniel Rodrigo Lopez, Andrea Kraus, Daniel Lopez, David Kraus, Markus Scholz, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Comparison of Three Imputation Methods for Groundwater Level Timeseries

Andrea Rinaldo

This study compares three imputation methods applied to the field observations of hydraulic head in subsurface hydrology. Hydrogeological studies that analyze the timeseries of groundwater elevations often face issues with missing data that may mislead bot ...

MDPI2023

Electromagnetic forces in the time domain

Olivier Martin, Karim Achouri, Andrei Kiselev

We look beyond the standard time-average approach and investigate optical forces in the time domain. The formalism is developed for both the Abraham and Minkowski momenta, which appear to converge in the time domain. We unveil an extremely rich - and by fa ...

Optica Publishing Group2022

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Andrea Zanoni

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022

Computing the daily reproduction number of COVID-19 by inverting the renewal equation using a variational technique

Jean-David Horacio Morel

The COVID-19 pandemic has undergone frequent and rapid changes in its local and global infection rates, driven by governmental measures or the emergence of new viral variants. The reproduction number Rt indicates the average number of cases generated by an ...

National Academy of Sciences2021

Synthetic electronic video containing a hidden image

Sabine Süsstrunk, Roger Hersch, Mahmut Sami Arpa

We present a method for hiding images in synthetic videos and reveal them by temporal averaging. We developed a visual masking method that hides the input image both spatially and temporally. Our masking approach consists of temporal and spatial pixel by p ...

2019

Meandering particle bunches and a link between averages of time series of particle counts and higher-order moments

Ambrogio Fasoli, Ivo Furno, Paolo Ricci, Marcelo Baquero Ruiz, Fabian Manke

Time-averaged spatially resolved measurements are used in many fields of physics to determine spatial distributions of a physical quantity. Although one could think that time averaging suppresses all information on time variation, there are some situations ...

2018

Revealing Information by Averaging

Sabine Süsstrunk, Mahmut Sami Arpa, Roger Hersch

We present a method for hiding images in synthetic videos and reveal them by temporal averaging. The main challenge is to develop a visual masking method that hides the input image both spatially and temporally. Our masking approach consists of temporal an ...

Optical Soc Amer2017

Shape-Constrained Uncertainty Quantification In Unfolding Steeply Falling Elementary Particle Spectra

Mikael Johan Kuusela

The high energy physics unfolding problem is an important statistical inverse problem in data analysis at the Large Hadron Collider (LHC) at CERN. The goal of unfolding is to make nonparametric inferences about a particle spectrum from measurements smeared ...

Inst Mathematical Statistics2017