Publications associées à Robust measures of scale

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

Springer2023

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

Kamiar Aminian, Anisoara Ionescu, Abolfazl Soltani, Francesca Salis

Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

BMC2023

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

Rachid Guerraoui, Nirupam Gupta, John Stephan, Youssef Allouah, Rafaël Benjamin Pinot

The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...

2023

CookieGraph: Understanding and Detecting First-Party Tracking Cookies

Carmela González Troncoso, Sandra Deepthy Siby

As third-party cookie blocking is becoming the norm in mainstream web browsers, advertisers and trackers have started to use first-party cookies for tracking. To understand this phenomenon, we conduct a differential measurement study with versus without th ...

New York2023

iSort enables automated complex microfluidic droplet sorting in an effort to democratize technology

Christoph Merten, Jatin Panwar

Fluorescence-activated droplet sorting (FADS) is a widely used microfluidic technique for high-throughput screening. However, it requires highly trained specialists to determine optimal sorting parameters, and this results in a large combinatorial space th ...

CELL PRESS2023

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

Fabio Nobile, Sebastian Krumscheid, Sundar Subramaniam Ganesh

In this work, we consider the problem of estimating the probability distribution, the quantile or the conditional expectation above the quantile, the so called conditional-value-at-risk, of output quantities of complex random differential models by the MLM ...

2022

Pollution mask for the continuous corrected particle number concentration data in 1 min resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020

Julia Schmale, Andrea Baccarini, Ivo Fabio Beck, Hélène Paule Angot

This dataset contains a pollution flag in 1 min time resolution. It is derived by the pollution detection algorithm (PDA) based on the corrected particle number concentration data (DOI upcoming) measured during the year long MOSAiC expedition from October ...

EPFL Infoscience2022

Improved Inference On Risk Measures For Univariate Extremes

Anthony Christopher Davison

We discuss the use of likelihood asymptotics for inference on risk measures in univariate extreme value problems, focusing on estimation of high quantiles and similar summaries of risk for uncertainty quantification. We study whether higher-order approxima ...

INST MATHEMATICAL STATISTICS-IMS2022

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Robust measures of scale

Small area vulnerability, household food insecurity and child malnutrition in Medellin, Colombia: results from a repeated cross-sectional study

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

CookieGraph: Understanding and Detecting First-Party Tracking Cookies

iSort enables automated complex microfluidic droplet sorting in an effort to democratize technology

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

Pollution mask for the continuous corrected particle number concentration data in 1 min resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020

Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks.

Improved Inference On Risk Measures For Univariate Extremes

Graph Chatbot

Chattez avec Graph Search

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

CookieGraph: Understanding and Detecting First-Party Tracking Cookies

iSort enables automated complex microfluidic droplet sorting in an effort to democratize technology

Small area vulnerability, household food insecurity and child malnutrition in Medellin, Colombia: results from a repeated cross-sectional study

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

On the Privacy-Robustness-Utility Trilemma in Distributed Learning

Pollution mask for the continuous corrected particle number concentration data in 1 min resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020

Towards Verifiable, Generalizable and Efficient Robust Deep Neural Networks.

Improved Inference On Risk Measures For Univariate Extremes