Publications associées à A comprehensive error rate for multiple testing

Transdiagnostic markers across the psychosis continuum: a systematic review and meta-analysis of resting state fMRI studies

Dimitri Nestor Alice Van De Ville, Farnaz Delavari

Psychotic symptoms are among the most debilitating and challenging presentations of severe psychiatric diseases, such as schizophrenia, schizoaffective, and bipolar disorder. A pathophysiological understanding of intrinsic brain activity underlying psychos ...

Frontiers Media Sa2024

Community-Aware Group Testing

Suhas Diggavi, Christina Fragouli, Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan

Group testing is a technique that can reduce the number of tests needed to identify infected members in a population, by pooling together multiple diagnostic samples. Despite the variety and importance of prior results, traditional work on group testing ha ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Seismic Testing of Adjacent Interacting Masonry Structures

Katrin Beyer, Andrea Penna, Igor Tomic

Masonry buildings form building aggregates around the world in historical centers, which developed as the layout of the city or village densified. In these aggregates, adjacent buildings can share structural walls, connected at the interfaces by interlocki ...

2023

On the slip burst amplitude cutoff in dislocation-rich microcrystals

Andreas Mortensen, Luciano Borasi

The plastic deformation of small-scale face-centered cubic metals exhibits intermittent slip burst events that appear on stress-strain curves as sudden strain jumps and/or load drops. These events are generally attributed to the avalanche-like cooperative ...

Pergamon-Elsevier Science Ltd2023

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Jean-Marc Vesin, Yann Prudat, Etienne Pruvot, Sasan Yazdani, Adrian Luca

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

BMC2022

Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia

Alessandra Griffa

The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural vari ...

ELSEVIER SCI LTD2022

Smart pooling: AI-powered COVID-19 informative group testing

Jorge Andres Madrid Wolff

Massive molecular testing for COVID-19 has been pointed out as fundamental to moderate the spread of the pandemic. Pooling methods can enhance testing efficiency, but they are viable only at low incidences of the disease. We propose Smart Pooling, a machin ...

Nature Portfolio2022

Testing For The Rank Of A Covariance Operator

Victor Panaretos

How can we discern whether the covariance operator of a stochastic pro-cess is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional dat ...

INST MATHEMATICAL STATISTICS-IMS2022

Interlaboratory Test Program to Determine the Precision of the R3 Test Method (ASTM C1897-20) for Measuring Reactivity of Supplementary Cementitious Materials

Karen Scrivener, Ruben Anton Snellings, Diana Londoño Zuluaga

The substitution of portland clinker by supplementary cementitious materials (SCMs) is one of the main avenues for the further decarbonization of cement production. To secure future SCM supplies, generic and performance-related test methods for SCMs are re ...

AMER SOC TESTING MATERIALS2022

Multiple testing with test statistics following heavy-tailed distributions

Zhiwen Jiang

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

EPFL2021

Group testing for connected communities

Suhas Diggavi, Christina Fragouli, Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan

In this paper, we propose algorithms that leverage a known community structure to make group testing more efficient. We consider a population organized in disjoint communities: each individual participates in a community, and its infection probability depe ...

MICROTOME PUBLISHING2021

The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms

David Atienza Alonso, Lara Orlandic, Tomas Teijeiro Campo

Overview Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. Th ...

Zenodo2021

FANOK: Knockoffs in Linear Time

Quentin Rebjock

We describe a series of algorithms that efficiently implement Gaussian model-X knockoffs to control the false discovery rate on large-scale feature selection problems. Identifying the knockoff distribution requires solving a large-scale semidefinite progra ...

SIAM PUBLICATIONS2021

Benchmark study of undrained triaxial testing of Opalinus Clay shale: Results and implications for robust testing

Lyesse Laloui, Alessio Ferrari, Alberto Minardi

Triaxial testing of argillaceous rocks and shales is significantly more challenging than conventional rock mechanical testing. The challenges are mainly related to the very low permeability of these geomaterials, and their sensitivity to exposure of atmosp ...

ELSEVIER2021

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high

Tamar Kohn, Joseph Chadi Benoit Lemaitre, Timothy R. Julian, Carola Bänziger, Xavier Fernandez Cassi, Federica Cariti, Alex Tunas Corzon

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this li ...

2021

A comprehensive error rate for multiple testing

Stephan Morgenthaler, Jean-Philippe Thiran, Djalel Eddine Meskaldji, Dimitri Nestor Alice Van De Ville

Over the last two decades, a large variety of type I error rates and control procedures have been proposed in the field of multiple hypotheses testing. This paper proposes a framework that includes many existing proposals by investigating procedures in whi ...

SPRINGER2020

Sampling strategy optimization to increase statistical power in landscape genomics: a simulation-based approach

Stéphane Joost, Estelle Rochat, Oliver Michele Selmoni, Elia Vajana, Annie Sandrine Guillaume

An increasing number of studies are using landscape genomics to investigate local adaptation in wild and domestic populations. The implementation of this approach requires the sampling phase to consider the complexity of environmental settings and the burd ...

2020

Testing of asymptomatic individuals for fast feedback-control of COVID-19 pandemic

Gabriel Aeppli

We argue that frequent sampling of the fraction ofa priorinon-symptomatic but infectious humans (either by random or cohort testing) significantly improves the management of the COVID-19 pandemic, when compared to intervention strategies relying on data fr ...

2020

Wannier90 as a community code: new features and applications

Nicola Marzari, Giovanni Pizzi, Marco Gibertini, Lorenzo Paulatto, Hyungjun Lee, Daniel John Gilles Marchand, Antimo Marrazzo, Samuel Poncé, Junfeng Qiao

Wannier90 is an open-source computer program for calculating maximally-localised Wannier functions (MLWFs) from a set of Bloch states. It is interfaced to many widely used electronic-structure codes thanks to its independence from the basis sets representi ...

2020

Learning and Adaptive Data Analysis via Maximal Leakage

Michael Christoph Gastpar, Ibrahim Issa, Amedeo Roberto Esposito

There has been growing interest in studying connections between generalization error of learning algorithms and information measures. In this work, we generalize a result that employs the maximal leakage, a measure of leakage of information, and explore ho ...

IEEE2019