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Concept

Identification (statistiques)

Publications associées (11)

Fading of brain network fingerprint in Parkinson's disease predicts motor clinical impairment

Enrico Amico

The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics. It is an approach able to recognize individuals, based on the brain network. It showed its applicability providing network features used to predict the cog ...

Wiley2023

Revisiting the General Identifiability Problem

Negar Kiyavash, Seyed Jalal Etesami, Ehsan Mokhtarian, Yaroslav Kivva

We revisit the problem of general identifiability originally introduced in [Lee et al., 2019] for causal inference and note that it is necessary to add positivity assumption of observational distribution to the original definition of the problem. We show t ...

2022

Functional registration and local variations: Identifiability, rank, and tuning

Victor Panaretos, Anirvan Chakraborty

We develop theory and methodology for the problem of nonparametric registration of functional data that have been subjected to random deformation (warping) of their time scale. The separation of this phase variation ("horizontal" variation) from the amplit ...

2021

Hierarchical B-spline complexes of discrete differential forms

Rafael Vazquez Hernandez

In this paper, we introduce the hierarchical B-spline complex of discrete differential forms for arbitrary spatial dimension. This complex may be applied to the adaptive isogeometric solution of problems arising in electromagnetics and uid mechanics. We de ...

2020

Functional data analysis by matrix completion

Marie-Hélène Descary

Traditional approaches to analysing functional data typically follow a two-step procedure, consisting in first smoothing and then carrying out a functional principal component analysis. The idea underlying this procedure is that functional data are well ap ...

EPFL2017

Biokinetic Model Identification via Extents of Reaction

Dominique Bonvin, Julien Léo Billeter, Sriniketh Srinivasan

Model structure selection and parameter identification for biokinetic modeling of biological wastewater treatment processes is broadly accepted to be a complicated task. Contributing factors include (i) nonlinear behavior, (ii) lack of knowledge, (iii) lac ...

2016

Snow hydrology signatures for model identification within a limits-of-acceptability approach

Bettina Schaefli

Discharge simulation from snow-dominated catchments seems to be an easy task. Any spatially explicit precipitation-runoff model coupled to a temperature-index snow model generally yields simulations that mimic well the observed daily discharges. The robust ...

Wiley-Blackwell2016

Predicting the Usefulness of Monitoring for Identifying the Behavior of Structures

Ian Smith, James-Alexandre Goulet

Structures can be better understood when measurement data are used to improve the modeling of structural behavior. Our capacity to interpret data depends on aspects such as the choice of model class, model parameters (and their range of possible values), a ...

American Society of Civil Engineers2013

Incremental model identification of gas-liquid reaction systems

Dominique Bonvin, Julien Léo Billeter, Sriniketh Srinivasan

Identification of kinetic models is an important task for monitoring, control and optimization of industrial processes. Kinetic models are often based on first principles, which describe the evolution of the states – numbers of moles, temperature and volum ...

2013

Probabilistic Model Falsification for Infrastructure Diagnosis

James-Alexandre Goulet

Most infrastructure in the western world was built in the second half of the 20th century. Transportation structures, water distribution networks and energy production systems are now aging and this leads to safety and serviceability issues. In situations ...

EPFL2012

A Local Nonlinear Model for the Approximation and Identification of a Class of Systems

Based on Volterra series the work presents a novel local nonlinear model of a certain class of linear-analytic systems. The special form of the expressions for the Laplace-domain Volterra kernels of such systems is exploited to obtain an approximation stru ...

Institute of Electrical and Electronics Engineers2009