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Related publications (31)

Multivariate time series forecasting for freeway networks

Semin Kwak

This dissertation introduces traffic forecasting methods for different network configurations and data availability. Chapter 2 focuses on single freeway cases. Although its topology is simple, the non-linearity of traffic features makes this prediction sti ...

EPFL2022

Information Processing Biases: The Effects of Negative Emotional Symptoms on Sampling Pleasant and Unpleasant Information

Steffen Alexander Herff

Although theories of emotion associate negative emotional symptoms with cognitive biases in information processing, they rarely specify the details. Here, we characterize cognitive biases in information processing of pleasant and unpleasant information, an ...

AMER PSYCHOLOGICAL ASSOC2022

Masksembles for Uncertainty Estimation

Pascal Fua, Pierre Bruno Baqué, Nikita Durasov, Timur Bagautdinov

Deep neural networks have amply demonstrated their prowess but estimating the reliability of their predictions remains challenging. Deep Ensembles are widely considered as being one of the best methods for generating uncertainty estimates but are very expe ...

2021

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips

Daniel Gatica-Perez, Skanda Muralidhar, Lakmal Buddika Meegahapola

Introduction Most evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. ...

2021

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Mehdi Gholam

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

Virtual reality to assess visual attraction and perceived interest to daylit scene variations

Marilyne Andersen, Caroline Karmann, Kynthia Chamilothori, Bahar Aydemir

Façades and light pattern composition have been shown to influence the spatial experience and physiological responses of humans [1,2]. The present study examines the effect of sunlight penetration and window size on fixations to the floor of the scene, and ...

2021

Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network

Satoshi Takahama, Amir Yazdani

Organic matter (OM) is a major constituent of fine particulate matter, which contributes significantly to degradation of visibility and radiative forcing, and causes adverse health effects. However, due to its sheer compositional complexity, OM is difficul ...

European Geosciences Union2021

Fast screening of covariates in population models empowered by machine learning

Jan Sickmann Hesthaven, Nadia Terranova

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

Characterizing human mobility patterns in rural settings of sub-Saharan Africa

Andrea Rinaldo, Theophile Mande, Francisco Javier Perez Saez

Human mobility is a core component of human behavior and its quantification is critical for understanding its impact on infectious disease transmission, traffic forecasting, access to resources and care, intervention strategies, and migratory flows. When m ...

eLIFE SCIENCES PUBL LTD2021

A general and efficient framework for atomistic machine learning

Félix Benedito Clément Musil

Over the last two decades, many technological and scientific discoveries, ranging from the development of materials for energy conversion and storage through the design of new drugs, have been accelerated by the use of preliminary in silico experiments, to ...

EPFL2021

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

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