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Concept

Causalité au sens de Granger

Publications associées (16)

Financial Risk Management with Machine Learning

Marc-Aurèle Antoine Divernois

This thesis consists of three applications of machine learning techniques to risk management. The first chapter proposes a deep learning approach to estimate physical forward default intensities of companies. Default probabilities are computed using artifi ...

EPFL2022

Gravitational causality and the self-stress of photons

Brando Bellazzini

We study causality in gravitational systems beyond the classical limit. Using on-shell methods, we consider the 1-loop corrections from charged particles to the photon energy-momentum tensor - the self-stress - that controls the quantum interaction between ...

Springer Nature2022

Daily Contributors of Tinnitus Loudness and Distress: An Ecological Momentary Assessment Study

Patrick Karl Alois Neff

BackgroundTinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a be ...

FRONTIERS MEDIA SA2022

Stimulus evoked causality estimation in stereo-EEG

Silvestro Micera, Fiorenzo Artoni

Objective. Stereo-electroencephalography (SEEG) has recently gained importance in analyzing brain functions. Its high temporal resolution and spatial specificity make it a powerful tool to investigate the strength, direction, and spectral content of brain ...

IOP PUBLISHING LTD2021

Measuring causality between collaborative and individual gaze metrics for collaborative problem-solving with intelligent tutoring systems

Kshitij Sharma, Jennifer Kaitlyn Olsen

When students are working collaboratively and communicating verbally in a technology-enhanced environment, the system cannot track what collaboration is happening outside of the technology, making it difficult to fully assess the collaboration of the stude ...

2021

Joint Fusion Learning of Multiple Time Series Prediction

Accurate traffic density estimations is essential for numerous purposes like the developing successful transit policies or to forecast future traffic conditions for navigation. Current developments in the machine learning and computer systems bring the tra ...

2019

Monitoring of the UHPFRC strengthened Chillon viaduct under environmental and operational variability

Eugen Brühwiler

Constructed in 1969, the Chillon viaducts constitute a vital component of the Swiss roadway network. The bridge deck was strengthened in 2015 by means of an Ultra High Performance Fiber Reinforced Cement-based Composite for alleviating the effects of deter ...

2020

Action Units and Their Cross-Correlations for Prediction of Cognitive Load during Driving

Jean-Philippe Thiran, Anil Yuce, Hua Gao, Gabriel Louis Cuendet

Driving requires the constant coordination of many body systems and full attention of the person. Cognitive distraction (subsidiary mental load) of the driver is an important factor that decreases attention and responsiveness, which may result in human err ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Correlation vs. Causality in Other-Triggered Upward Lightning in Tower Flashes

Farhad Rachidi-Haeri, Marcos Rubinstein, Aleksandr Smorgonskii

Upward lightning flashes from towers are sometimes preceded by other lightning activity in the vicinity of the tower. This observation has led to a classification of upward tower lightning into self-initiated, which are not preceded by nearby lightning act ...

Ieee2016

Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation

Tilo Schwalger

We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike int ...

Springer2015

Adaptive Image Resizing Based on Continuous-Domain Stochastic Modeling

Michaël Unser, Aurélien Bourquard, John Paul Ward, Hagay Kirshner

We introduce an adaptive continuous-domain modeling approach to texture and natural images. The continuous-domain image is assumed to be a smooth function, and we embed it in a parameterized Sobolev space. We point out a link between Sobolev spaces and sto ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Is Uniqueness Lost for Under-Sampled Continuous-Time Auto-Regressive Processes?

Michaël Unser, John Paul Ward, Hagay Kirshner

We consider the problem of sampling continuous-time auto-regressive processes on a uniform grid. We investigate whether a given sampled process originates from a single continuous-time model, and address this uniqueness problem by introducing an alternativ ...

IEEE Institute of Electrical and Electronics Engineers2012

Robust Value at Risk Prediction

Loriano Mancini

This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that contr ...

Oxford University Press2011

Robust Multivariate and Nonlinear Time Series Models

Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables lik ...

EPFL2010

Estimation of the depth of anaesthesia from interacting physiological oscillators

Nowadays, physiological monitoring is imperative for the safety of medical operations. However, systems which monitor the depth of anaesthesia are still far from reliable, such that still some patients may experience the trauma of remaining conscious under ...

EPFL2008

A century-old debate on protein aggregation and neurodegeneration enters the clinic

Hilal Lashuel

The correlation between neurodegenerative disease and protein aggregation in the brain has long been recognized, but a causal relationship has not been unequivocally established, in part because a discrete pathogenic aggregate has not been identified. The ...

2006