Concept

Parametric equation

Publications associées (75)

This code is used for developing the project entitled “Study on conformal antennas, proof of concept prototype for a UAV”, from the aspects of theory, design, and implementation. This code aims to speed up the investigation of an arbitrary phased array ant ...

Zenodo2024

Data-enabled Predictive Control for Empty Vehicle Rebalancing

Nikolaos Geroliminis, Giancarlo Ferrari Trecate, Pengbo Zhu

A critical operational challenge in Mobility-on-demand systems is the problem of imbalance between vehicle supply and passenger demand. However, conventional model-based methods require accurate parametric system models with complex nonlinear dynamics that ...

IEEE2023

Robust numerical integration on curved polyhedra based on folded decompositions

Annalisa Buffa, Pablo Antolin Sanchez, Xiaodong Wei

We present a novel method to perform numerical integration over curved polyhedra enclosed by high-order parametric surfaces. Such a polyhedron is first decomposed into a set of triangular and/or rectangular pyramids, whose certain faces correspond to the g ...

ELSEVIER SCIENCE SA2022

Inspired by Sibson’s alpha-mutual information, we introduce a new parametric class of universal predictors. This class interpolates two well-known predictors, the mixture estimator, that includes the Laplace and the Krichevsky-Trofimov predictors, and the ...

2022

Design and evaluation of digital tools to expand experience in vocational education

Kevin Gonyop Kim

Vocational education and training (VET) is the most popular form of upper-secondary education in Switzerland, with more than two-thirds of the teenagers enrolling in a VET program after finishing their compulsory education. The vast majority of the Swiss V ...

EPFL2022

Parametric Estimation For Functional Autoregressive Processes On The Sphere

The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as weak consistency ...

2022

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Davide Pradovera

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

EPFL2021

In vivo macromolecule signals in rat brain 1 H‐MR spectra at 9.4T: Parametrization, spline baseline estimation, and T 2 relaxation times

Lijing Xin, Cristina Ramona Cudalbu, Bernard Lanz, Dunja Simicic, Veronika Rackayová

Purpose Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) 1H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high fiel ...

2021

Shape Reconstruction by Learning Differentiable Surface Representations

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík, Erhan Gündogdu

Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric representations. Unfortunately, they offer no control over the deformations of the su ...

2020

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Tom Hilbert, Erick Jorge Canales Rodriguez, Elda Fischi Gomez, Marco Pizzolato, Gian Franco Piredda, Thomas Yu, Cristina Granziera, Muhamed Barakovic

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

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