Publications related to Exploratory Analysis of Endogeneity in Discrete Choice Models

Distributional Regression and Autoregression via Optimal Transport

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia

Photoplethysmography (PPG) is a widely emerging method to assess vascular health in humans. The origins of the signal of reflective PPG on peripheral arteries have not been thoroughly investigated. We aimed to identify and quantify the optical and biomecha ...

MDPI2023

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

Stéphane Joost

Summary Background Malnutrition and food insecurity might be driven not only by individual factors but also by contextual conditions, such as area-level deprivation or vulnerability. This study aimed to analyze the association between area-level vulnerabil ...

2023

Testing and nonlinear modelling of industrialized light-frame wooden diaphragms including optimized nailing and nonstructural sheathing

Edisson Xavier Estrella Arcos

This article presents the outcomes of a large project towards the investigation of the lateral performance of full-scale industrialized light-frame wooden diaphragms. 10 full-scale diaphragms of 3.6 m by 2.4 m were tested under in-plane lateral loading (mo ...

Oxford2023

Distribution-on-distribution regression via optimal transport maps

Victor Panaretos, Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...

OXFORD UNIV PRESS2022

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

Gaussian Process Regression for Materials and Molecules

Michele Ceriotti, David Mark Wilkins

We provide an introduction to Gaussian process regression (GPR) machinelearning methods in computational materials science and chemistry. The focus of the present review is on the regression of atomistic properties: in particular, on the construction of in ...

AMER CHEMICAL SOC2021

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Nikolaos Geroliminis, Emmanouil Barmpounakis

The work proposes a multi-modal regional mean speed regression analysis for the city network of Athens, Greece. The dataset from pNUEMA experiment is used in the present context. Accumulations and mean speeds of different modes are estimated and compared t ...

2021

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Francesca Criscuolo

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

2021

Exploratory Analysis of Endogeneity in Discrete Choice Models

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Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

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

Testing and nonlinear modelling of industrialized light-frame wooden diaphragms including optimized nailing and nonstructural sheathing

Distribution-on-distribution regression via optimal transport maps

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

Gaussian Process Regression for Materials and Molecules

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Distribution-on-distribution regression via optimal transport maps

Gaussian Process Regression for Materials and Molecules

Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

Distributional Regression and Autoregression via Optimal Transport

Bayes-optimal Learning of Deep Random Networks of Extensive-width

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

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

Testing and nonlinear modelling of industrialized light-frame wooden diaphragms including optimized nailing and nonstructural sheathing

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models