Publications related to Stepwise regression

Related publications (28)

Model reduction of coupled systems based on non-intrusive approximations of the boundary response maps

Jan Sickmann Hesthaven, Niccolo' Discacciati

We propose a local, non -intrusive model order reduction technique to accurately approximate the solution of coupled multi -component parametrized systems governed by partial differential equations. Our approach is based on the approximation of the boundar ...

Elsevier Science Sa2024

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Seyedbehzad Bozorgtabar

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Elsevier2024

Aerodynamic modeling of a delta-wing UAV for model-based navigation

Jan Skaloud, Pasquale Longobardi

This study aims to identify an optimal, as well as practical, parametric structure for a delta-wing UAV aerodynamic model for the purpose of model-based navigation. We present a comprehensive procedure for characterizing the aerodynamics of this platform, ...

2024

Networks with correlated edge processes

Mária Süveges, Sofia Charlotta Olhede

This article proposes methods to model non-stationary temporal graph processes motivated by a hospital interaction data set. This corresponds to modelling the observation of edge variables indicating interactions between pairs of nodes exhibiting dependenc ...

OXFORD UNIV PRESS2023

Do we really measure what we think we are measuring?

Michael Herzog, Janir Nuno Ramos Antunes Da Cruz, Simona Adele Garobbio, Dario Alejandro Gordillo Lopez

Tests used in the empirical sciences are often (implicitly) assumed to be representative of a given research question in the sense that similar tests should lead to similar results. Here, we show that this assumption is not always valid. We illustrate our ...

Cell Press2023

One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction

Mathias Josef Payer

Fuzzing is the de-facto default technique to discover software flaws, randomly testing programs to discover crashing test cases. Yet, a particular scenario may only care about specific code regions (for, e.g., bug reproduction, patch or regression testing) ...

ASSOC COMPUTING MACHINERY2022

SporTran: A code to estimate transport coefficients from the cepstral analysis of (multivariate) current time series

Loris Ercole

SporTran is a Python utility designed to estimate generic transport coefficients in extended systems, based on the Green-Kubo theory of linear response and the recently introduced cepstral analysis of the current time series generated by molecular dynamics ...

ELSEVIER2022

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

Improving the efficiency of identifying malignant pulmonary nodules before surgery via a combination of artificial intelligence CT image recognition and serum autoantibodies

Jiancheng Yang

ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...

SPRINGER2022

Mesh d-refinement: a data-based computational framework to account for complex material response

Jean-François Molinari, Antonio Joaquin Garcia Suarez, Sacha Zenon Wattel

Model-free data-driven computational mechanics (DDCM) is a new paradigm for simulations in solid mechanics. The modeling step associated to the definition of a material constitutive law is circumvented through the introduction of an abstract phase space in ...

2023

Hubbard U through polaronic defect states

Alfredo Pasquarello, Stefano Falletta

Since the preliminary work of Anisimov and co-workers, the Hubbard corrected DFT+U functional has been used for predicting properties of correlated materials by applying on-site effective Coulomb interactions to specific orbitals. However, the determinatio ...

NATURE PORTFOLIO2022

Improving sample and feature selection with principal covariates regression

Michele Ceriotti, Edgar Albert Engel, Benjamin Aaron Helfrecht

Selecting the most relevant features and samples out of a large set of candidates is a task that occurs very often in the context of automated data analysis, where it improves the computational performance and often the transferability of a model. Here we ...

2021

Fast screening of covariates in population models empowered by machine learning

Jan Sickmann Hesthaven

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervise ...

2021

Sparsest piecewise-linear regression of one-dimensional data

Michaël Unser, Julien René Fageot, Thomas Jean Debarre, Quentin Alain Denoyelle

We study the problem of one-dimensional regression of data points with total-variation (TV) regularization (in the sense of measures) on the second derivative, which is known to promote piecewise-linear solutions with few knots. While there are efficient a ...

Elsevier2021

Real-world gait speed estimation, frailty and handgrip strength: a cohort-based study

Kamiar Aminian, Anisoara Ionescu, Abolfazl Soltani

Gait speed is a reliable outcome measure across multiple diagnoses, recognized as the 6th vital sign. The focus of the present study was on assessment of gait speed in long-term real-life settings with the aim to: (1) demonstrate feasibility in large cohor ...

Nature Portfolio2021

Counting using deep learning regression gives value to ecological surveys

Devis Tuia, Benjamin Alexander Kellenberger

Many ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or lab is limited. However, an increasing number of works uses digital imagery, whi ...

Nature Research2021

How do visual skills relate to action video game performance?

Michael Herzog, Aline Françoise Cretenoud, Oh-Hyeon Choung, Arthur Barakat

It has been claimed that video gamers possess increased perceptual and cognitive skills compared to non-video gamers. Here, we examined to which extent gaming performance in CS:GO (Counter-Strike: Global Offensive) correlates with visual performance.We tes ...

Association for Research in Vision and Ophthalmology2021

Tenants’ residential mobility in Switzerland: the role of housing functions

Claudia Rebeca Binder Signer, Anna Pagani, Ivo Philippe Baur

The interaction between residential preferences and dwellings is a complex system whose function thus far remains insufficiently explored. In this paper, we investigate housing functions as orchestrators of households’ residential mobility in the context o ...

2021

Postmortem memory of public figures in news and social media

Robert West

Deceased public figures are often said to live on in collective memory. We quantify this phenomenon by tracking mentions of 2,362 public figures in English-language online news and social media (Twitter) 1 y before and after death. We measure the sharp spi ...

National Academy of Sciences2021

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Jan Sickmann Hesthaven, Mengwu Guo, Mariella Kast

We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. From a collection of low-fidelity (LF) snapshots, parameter locations are extracted for the e ...

ELSEVIER SCIENCE SA2020